How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of...

American Economic Review 2015 105(4) 1478ndash1508 httpdxdoiorg101257aer20130360

1478

How Elastic Are Preferences for Redistribution Evidence from Randomized Survey Experiments dagger

By Ilyana Kuziemko Michael I Norton Emmanuel Saez and Stefanie Stantcheva

We analyze randomized online survey experiments providing inter-active customized information on US income inequality the link between top income tax rates and economic growth and the estate tax The treatment has large effects on views about inequality but only slightly moves tax and transfer policy preferences An exception is the estate taxmdashinforming respondents of the small share of decedents who pay it doubles support for it The small effects for all other pol-icies can be partially explained by respondentsrsquo low trust in govern-ment and a disconnect between concerns about social issues and the public policies meant to address them (JEL D31 D72 H23 H24)

The past several decades have seen a large increase in income concentration in the United States While the top 1 percent of families captured 90 percent of total pre-tax income in 1970 that share rose to 224 percent by 20121 More recent work has documented a corresponding trend for wealth concentration the top 01 percent share of wealth has grown from 8 percent in the mid-1970s to 22 percent in 2012 (Saez and Zucman 2014) These trends have not gone unnoticed at least by some The Occupy Wall Street movement popularized the term ldquothe 1 percentrdquo Recently President Obama has called ldquoa dangerous and growing inequalityrdquo the ldquodefining challenge of our timerdquo a sentiment echoed by the CEO of Goldman Sachs who told an interviewer that ldquotoo much of the GDP of the country has gone to too few of the peoplerdquo2

There is a large theoretical literature on the link between inequality and redistribu-tion The most widely used median-voter model predicts that a widening gap between the average and the median income should lead to an increase in redistribution as politicians respond to the median voterrsquos preferences (Meltzer and Richard 1981)

1 See the updates to Table A3 of Piketty and Saez (2003) httpelsaberkeleyedu~saezTabFig2012prelxls2 See httpwwwwhitehousegovthe-press-office20131204remarks-president-economic-mobility (accessed

December 1 2014) and httpthinkprogressorgeconomy201406133448679goldman-sachs-income-inequality (accessed December 1 2014) respectively

Kuziemko Princeton University Princeton NJ 08544 (e-mail kuziemkoprincetonedu) Norton Harvard Business School Soldiers Field Road Boston MA 02163 (e-mail mnortonhbsedu) Saez University of California 530 Evans Hall 3880 Berkeley CA 94720 (e-mail saezeconberkeleyedu) Stantcheva Harvard University Littauer Center 226 Cambridge MA 02138 (e-mail sstantchevafasharvardedu) We thank Raj Chetty Amy Finkelstein Ray Fisman Lawrence Katz Wojciech Kopczuk James Poterba Andrea Prat Jonah Rockoff four anonymous referees and numerous seminar and conference participants for helpful comments and dis-cussions Pauline Leung provided outstanding research assistance Financial support from the Center for Equitable Growth at UC Berkeley the MacArthur Foundation and NSF Grant SES-1156240 is gratefully acknowledged

dagger Go to httpdxdoiorg101257aer20130360 to visit the article page for additional materials and author disclosure statement(s)

1479KuziemKo et al How elastic are Preferences for redistributionVol 105 no 4

By contrast top income tax rates as well as inheritance tax rates have fallen in the United States during this period3 While for institutional reasons the policy views of the majority might be ignored by policymakers (Bartels 2009) even more chal-lenging to the modelrsquos predictions is that survey respondents themselves show no increased demand for redistribution since the 1970s4 If anything the General Social Survey shows that there has been a slight decrease in stated support for redistribu-tion in the United States since the 1970s even among those who self-identify as having below average income (see Figure 1) These trends have led commentators to suggest that US residents simply do not care about rising inequality5

There are alternative explanations Americans may be unaware of the extent or growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011) this information may not be sufficiently salient or they are skeptical about the gov-ernmentrsquos ability to redistribute effectively6 In this paper we extensively examine

3 For top income tax rates see Piketty Saez and Stantcheva (2014) and for estate taxes see IRS calculations at httpwwwirsgovpubirs-soininetyestatepdf

4 See eg Kenworthy and McCall (2008) for evidence from a variety of OECD countries that saw increases in inequality but no corresponding increase in redistributive demand

5 As Newsweek put it in 2001 ldquoIf Americans couldnrsquot abide rising inequality wersquod now be demonstrating in the streetsrdquo Samuelson Robert J 2001 ldquoIndifferent to inequalityrdquo Newsweek May 7 p 45

6 A number of alternative theoretical models make different predictions than the median voter model Corneo and Gruumlner (2000) propose a model with status effects where the middle class opposes redistribution when this leads to more social competition with bottom income earners Alesina and Angeletos (2005) and Piketty (1995) show that different beliefs on the role of effort versus luck in success can lead to multiple redistributive equilibria Beacutenabou and Ok (2001) show that the prospect for upward mobility can limit the desire for redistribution There is also a wide empirical literature on the determinants of preferences for redistribution (see eg Corneo and Gruumlner 2002 Guillaud 2013 and Senik 2009 for evidence from cross-country survey data)

35

4

45

5

55

Gov

ernm

ent s

houl

d re

duce

inco

me

diffe

renc

es (1

minus7)

1980 1990 2000 2010

All respondents Self-identified below average income

Figure 1 The Government Should Reduce Income Differences (Scale from 1ndash7 GSS)

Notes This figure depicts responses since 1978 in the US General Social Survey (GSS) on whether the government should reduce income differences The empty diamond series is for all respondents while the full circle series is for respondents with below average income Regression fits are depicted for each series The graph uses the eqwlth vari-able from the GSS (though subtracts it from 8 so that it is increasing in support for redistribution)

1480 THE AMERICAN ECONOMIC REVIEW ApRIl 2015

these explanations We conduct a series of randomized survey experiments using Amazonrsquos Mechanical Turk (mTurk) mTurk is a rapidly growing online platform that can be used to carry out social and survey experiments (see Horton Rand and Zeckhauser 2011 and Paolacci Chandler and Ipeirotis 2010) In our initial set of experiments comprising just over 4000 respondents one-half of respondents were randomized into an ldquoomnibusrdquo treatment providing interactive personalized infor-mation on US income inequality the historical correlation between top income tax rates and economic growth and the incidence of the estate tax Both control and treatment groups then reported their views on inequality redistributive policies and government more generally We then conducted follow-up experiments with about 6000 new respondents to analyze potential mechanisms behind the initial results for a total of approximately 10000 respondents7

Our treatments exploit the flexibility of the mTurk platform to include several features that heighten the salience of the information we present First some of the information we present is customized For example we ask individuals their household income allowing us to show them their place in the income distribution as well as their counterfactual income level had aggregate income growth since 1980 been distributed more equally (so as to leave inequality unchanged) In other parts of the survey we customize information based on respondentsrsquo own household composition8 Second some of the information is interactivemdashfor example our sur-vey allows respondents to enter different household income levels and the software survey application provides the corresponding percentile so that the income distri-bution can be transparently explored

The initial survey experiment provides several findings we believe to be novel relative to existing literature the first part of the paper provides a descriptive analy-sis of these results First we find that respondentsrsquo concern about inequality is very elastic to information for example the treatment increases the share agreeing that inequality is a ldquovery serious problemrdquo by over 35 percent Put differently the treat-ment effect is equal to roughly 36 percent of the gap between self-identified liberals and self-identified conservatives on this question By contrast while there are some effects on policy preferences such as top income tax rates the minimum wage and food stamps (always in the ldquoexpectedrdquo direction) they are small and often insignif-icant despite the large sample size

The only exception is the estate tax we find that providing information on the (small) share of estates subject to the tax more than doubles respondentsrsquo support for increasing it Focusing on the estate tax result we attempt to make progress on two longstanding critiques about survey analysis that the effects are ephemeral and unrelated to actual behavior We benefit from the mTurk technology and re-survey respondents one month later the estate tax effect is virtually unchanged We also find that the treatment significantly increases the share of respondents who say they would send a petition to one of the US senators from their state to raise the estate tax

7 Survey questions and treatments are all available in the online Appendix8 Recent work has highlighted the potential power of customizing information in interventions For example

Hoxby and Turner (2013) credit the customized nature of the information they present to students for the large effects their intervention had on college application decisions

The second half of the paper explores the mechanisms behind the large estate tax effects and the muted response for any other policy outcome Of course other explanations may exist and as such we do not view our attempts to tease out the mechanisms behind the main results as definitive Consistent with past work we find that respondents are wildly misinformed about the share of decedents subject to the estate tax which appears to account for the large effects We further show that the estate tax effect remains strong even when we take steps to decrease the salience and emotional content of the information provided further proof that more informa-tion on this issue has large effects

We test three potential explanations for the small effects for other policies limited trust in government an overly ldquoclinicalrdquo presentation of information and respon-dentsrsquo inability to connect their concerns on a given issue with the public policies meant to address it

The first potential explanation is that distrust in government inhibits respondents from translating concern for inequality into support for redistribution by the gov-ernment Several results from the original survey experiment point in this direc-tion First our initial treatment significantly decreases trust in government When reminded of the extent of inequality (which even control group respondents view as a problem) those in the treatment group appear to at least partially blame the gov-ernment perhaps thinking that if politicians ldquolet things get this badrdquo they cannot be trusted to fix it Second beyond any treatment effect the level of government trust among our sample of mTurk respondents is very low over 89 percent agree that ldquoPoliticians in Washington work to enrich themselves and their largest campaign contributors instead of working for the benefit of the majority of citizensrdquo with 47 percent ldquostronglyrdquo agreeing It is thus perhaps not surprising that even when the treatment increases respondentsrsquo concern with inequality they remain reluctant to increase support for government redistributive policies

In a follow-up survey experiment we provide direct evidence for the effect of trust in government on respondentsrsquo policy preferences We first asked a small pilot group to answer open-ended questions on their views of government the main theme that emerges is that politicians are believed to work to enrich themselves and their wealthiest campaign donors We then used these answers to develop ldquoprimesrdquo (eg asking respondentsrsquo opinions about lobbyists or the Wall Street bailout) that signifi-cantly lowered trust in government without significantly changing views about the extent of inequality or poverty Therefore the treatment isolates the causal effect of decreasing trust in government We find that the treatment significantly lowers support for all poverty-alleviation policies with the exception interestingly of the minimum wagemdasha program that does not involve direct transfers from the govern-ment Support for top tax rates generally falls as well (though only some of these effects are significant) and respondents elevate ldquoprivate charityrdquo over government policies in a list of the best ways to combat inequality This analysis provides to our knowledge the first direct evidence on the causal effects of trust in government on policy preferences and is particularly relevant given the historically low regard with which Americans currently view their government9

9 See analysis from Gallup httpwwwgallupcompoll164663americans-trust-government-generally- down-yearaspx (accessed December 1 2014) The General Social Survey also shows a strongly negative trend Related

Besides distrust muting the policy effects of our treatment we explore two other potential explanations for the small effects in the original survey experiment As Brader (2005) and others argue policy preferences might respond more to emo-tional than factual appeals We thus develop a treatmentmdashagain interactive and customizedmdashdesigned to evoke empathy for households at the poverty line Just as in the initial survey experiment the treatment significantly increases respondentsrsquo tendency to view inequality and poverty as ldquoserious problemsrdquo but has almost no effect on policy preferences

We find more support for a third explanation the idea in Bartels (2005) that the public fails to connect concern for inequality with actual public policy measures To test this idea we repeat much of the information in the ldquoemotional appealrdquo treat-ment but then show respondents concretely the resources provided to such fami-lies through government programs including the minimum wage and food stamps Therefore the treatment directly connects poverty and inequality with policies meant to address them Emphasizing this connection appears important treatment respondents significantly increase their support for the minimum wage as well as most of the poverty-alleviation programs that we survey We view this result as potentially complementary to the trust results given the low baseline levels of trust it appears to be the case that policy preferences can only be moved if respondents are explicitly reminded of efficacious examples of government intervention

We believe our findings make several contributions to the understanding of how individuals formmdashand changemdashtheir redistributive preferences Compared to most informational interventions that merely provide a fixed set of facts to respondents our informational treatments were interactive and customizedmdashwhile perhaps not providing a strict upper bound on the effects of information on preferences our results do suggest that most policy preferences are hard to move This finding echoes Luttmer and Singhal (2011) that redistributive preferences may have ldquocul-turalrdquo determinants that are very stable over time

Our results also highlight the potential role of mistrust of government in limit-ing the publicrsquos enthusiasm for policies they would otherwise appear to support a subject that has garnered limited attention in the economics literature An exception is Sapienza and Zingales (2013) who find that a major reason respondents support auto fuel standards over a gasoline-tax-and-rebate scheme is not because they mis-understand the incidence of fuel standards but because they simply do not trust the government to actually rebate them their money

More generally our paper relates to the literature on the determinants of redistrib-utive preferences to which political scientists sociologists psychologists and pub-lic economists have all contributed Many papers in this literature use survey data to relate individual traits to redistributive preferences and do not as we do take an experimental approach Alesina and Ferrara (2005) Alesina and Giuliano (2011) and Fong (2001) show that respectively prospects for future income mobility past experience of misfortune and beliefs about equality of opportunity predict redistrib-utive preferences Other papers have examined how situational factors (employment status neighborhood characteristics) predict preferences (see eg Margalit 2013

to our finding Yamamura (2014) finds that above average income respondents in Japan are more likely to support redistribution when trust in government in their residential area is high

Luttmer 2001) Singhal (2008) uses OECD survey data to show that people do not necessarily favor low tax rates at income levels close to theirs suggesting that redis-tributive preferences are not completely determined by self-interest

As in our paper some researchers have estimated the effects of randomized informational treatments on policy preferences10 The evidence from these efforts is mixed Sides (2011) finds that providing information on the very small number of individuals affected by the estate tax drastically decreases support for its repeal results that we replicate with our data Cruces Perez-Truglia and Tetaz (2013) find that showing poor individuals their actual place in the income distribution increases their support for policies that target poverty as most overestimate their income On the other hand Kuklinski et al (2003) find that providing (accurate) information on the demographic composition of welfare recipients and the share of the federal bud-get dedicated to welfare payments has no effect on respondentsrsquo preferences despite the fact that their initial beliefs are wildly incorrect11 We examine a wide variety of redistributive policy outcomes indeed we find that the responsiveness of views on the estate tax appears to be an outlier and other outcomes suggest a far more modest effect of information on redistributive preferences

As noted our research is part of a small but growing set of papers using online platforms Researchers have used these platformsmdashmost often mTurkmdashto have respondents play public goods games (eg Rand and Nowak 2011 Suri and Watts 2010) interact in online labor markets (Amir Rand and Gal 2012 Horton Rand and Zeckhauser 2011) or simply answer non-experimental survey questions on views about policy and social preferences (Weinzierl 2012 Saez and Stantcheva 2013) We summarize our experience conducting survey experiments on mTurk in the online methodological Appendix which we hope can be of use to future researchers utilizing this platform

The paper proceeds as follows Section I introduces the initial survey instrument and data collection procedures Section II describes the data Section III presents the main results of the survey experiment In Section IV we explore mechanisms behind the large effects of information on views about the estate tax and why most other effects were so limited reporting methods and results from four follow-up survey experiments Finally in Section V we suggest directions for future work and offer concluding thoughts All our online surveys data and programs are available in the online Appendix

I The Main Survey Experiment

The main experiment was implemented in four separate rounds from January 2011 to August 2012 For expositional clarity to distinguish this initial experiment from the follow-up work we describe in Section IV we refer to these four initial rounds of surveys as the ldquoomnibusrdquo treatment surveys The omnibus treatment sur-veys had the following structure (i) background socioeconomic questions including

10 While not related to policy preferences there is a small literature on how information treatments affect indi-vidualsrsquo ability to better navigate policies such as social security (Liebman and Luttmer 2011)

11 Related but distinct from informational treatments are priming and presentational treatments (see eg Savani and Rattan 2012 on the effect of priming free will and McCaffery and Baron 2006 on the effects of presenting taxes in absolute or percentage terms)

typical demographic questions as well as political leanings (ii) randomized treat-ment providing information on inequality and tax policy (shown solely to the treat-ment group) and (iii) questions on views on inequality tax and transfer policies and government more generally12

A Data Collection

Surveys were openly posted on mTurk with a description stating that the survey paid $150 for approximately 15 minutes ie a $6 hourly wage Respondents were free to drop out any time or take up to one hour to answer all questions As a com-parison the average effective wage on mTurk according to Amazon is around $480 per hour and most tasks on mTurk are short (less than one hour)13

Several steps were taken to ensure the validity of the results First there are many foreign workers on mTurk especially from Asia In addition to requiring respon-dents to confirm their US residency on the consent form we also had Amazon show the survey only to workers who had US addresses Second to further discourage foreign workers we tried to launch our surveys during East Coast daylight hours (and to reduce heterogeneity only on workdays) Third to exclude robots only workers with a past completion rate of at least 90 percent were allowed to take the survey Fourth as our survey comprises many rounds we screen out workers who had participated in a previous round of the survey Fifth respondents were told that payment would be contingent on completing the survey and providing a password visible only at completion Finally to discourage respondents from skipping mind-lessly through the pages pop-up windows with an encouragement to answer all questions appeared as prompts whenever a question was left blank

B The Omnibus Information Treatment

In general the goal of the information treatments was to provide a large ldquoshockrdquo to individualsrsquo knowledge about inequality and redistributive policies rather than to provide a PhD-level nuanced discussion about say the underlying causes of inequal-ity or the trade-off between equality and efficiency Hence some of the treatments we display will seem overly simplified to an economics audience but it should be kept in mind that our goal in the initial experiment is to test whether any treatment can move redistributive preferences thus we erred on the side of presenting information we thought would indeed move those preferences As noted in the introduction we took steps to make the information both interactive and customized to each respondent

The treatment had three basic parts First treatment respondents saw interac-tive information on the current income distributionmdashthey were asked to input their household income and were then told what share of households made more or less than their household We also asked them to find particular points in the

12 The online Appendix provides a complete description of the experiment with the questions for each round of the main experiments and the follow-up experimental rounds discussed later in the paper

13 To gauge the external validity of the mTurk results we gathered data for round 3 using CampT Marketing (httpwwwctmarketinggroupcom) (accessed December 1 2014) As noted in Section III effects are stable across rounds suggesting that respondents from the two platforms respond similarly to the treatment Per-participant costs for CampT are roughly five times higher than for mTurk

distributionmdashthey were asked to find the median and the ninetieth and ninety-ninth percentiles and were encouraged to ldquoplay aroundrdquo with the application Online Appendix Figure 2 presents a screen shot14

The second part focused not on the current distribution but a counterfactual respondents entered their current income and were then shown what they ldquowould have maderdquo had economic growth since 1980 been evenly shared across the income distribution (ie had the level of inequality stayed the same as in 1980) Of course this exercise abstracts away from the trade-off between efficiency (economic growth) and equality that would certainly exist at very high levels of taxation The interactive application allowed them to find this counterfactual value for any point of the current income distribution Online Appendix Figure 4 presents a screen shot

The third part of the treatment focused on redistributive policies To emphasize that higher income taxes on the well-off need not always lead to slower economic growth we presented respondents a figure showing that at least as a raw correlation economic growth measured by average real pre-tax income per family from tax return data has been slower during periods with low top tax rates (1913ndash1933 and 1980ndash2010) than with high top tax rates (1933ndash1980) Online Appendix Figure 3 presents a screen shot Similarly we also presented a slide on the estate tax empha-sizing that it currently only affects the largest 01 percent of estates and that it favors intergenerational mobility Online Appendix Figure 4 shows a screen shot

Readers can directly experience these informational treatments online at the link below15 We describe the additional treatments in the follow-up surveys in Section IV

II Data

A Summary Statistics

Table 1 shows characteristics of the sample who completed the omnibus treat-ment survey rounds (we discuss attrition below) We compare these summary sta-tistics to a nationally representative sample of US adults contacted by a Columbia Broadcasting Company (CBS) poll in 2011 which we choose both because it was conducted around the same time as our surveys and asks very similar questions16 We also compare it to a more representative (though far more expensive) online panel survey gathered by RAND the American Life Panel (ALP)17

14 As detailed in online Appendix Table 1 we also ask treatment respondents six ldquobasic comprehensionrdquo ques-tions to determine if the information was confusing With one exception each question exhibits at least 80 percent comprehension Moreover more than 74 percent of respondents answer at least five of the six questions correctly There are no differential treatment effects by comprehension level (results available upon request) not surprising given that comprehension is at a fairly high (and uniform) level

15 See httpshbsqualtricscomSESID=SV_77fSvTy12ZSBihn Note that the control group went straight from the background questions to the outcome measures (starting with the preferred tax rates sliders)

16 Note that the CBS sample is not as representative as the traditional surveys used by economists such as the Current Population Survey or the American Community Survey However these two surveys do not have questions on past voting behavior or political preferences so we rely on the admittedly less representative CBS survey

17 The ALP currently costs researchers $3 per subject per minute compared to roughly $010 per subject per minute for our mTurk surveys The ALP survey is also limited in sample size

Our sample is younger more educated and has fewer minorities It is more lib-eral with a higher fraction reporting having supported President Obama in the 2008 presidential election18

Table 2 shows summary statistics on demographic and policy views for self-re-ported liberals (column 1) and conservatives (column 2) from our control group (so that responses are not contaminated by the information treatment) as well as the entire control group (column 3) As expected conservatives are older more white and more likely to be married They prefer lower taxes on the rich and a less generous safety net Such contrasts are useful to scale the magnitude of our effects We will often discuss treatment effects both in absolute terms and as a percentage of the liberal-versus-conservative differences reported in Table 2 For convenience we refer to this difference as the ldquopolitical gaprdquo for a given outcome variable

B Survey Attrition

The omnibus survey experiment had an overall attrition rate of 22 percent which includes those who attritted as early as the consent page For those who remained online long enough to be assigned a treatment status attrition was 15 percent

As online Appendix Table 2 shows attrition is not random though it is unre-lated to 2008 voting preferences and liberal versus conservative policy views (the variables most highly correlated with our outcome variables) The online survey for the treatment group was by necessity different from the online survey for

18 As a robustness check we created weights to match our mTurk sample in column 1 to the CBS poll in col-umn 2 with respect to the 32 cells based on gender (2) times age brackets (2) times white versus non-white (2) times college degree indicator (2) times Supported Obama in 2008 (2) Reweighting has no appreciable effects on the results in Tables 4 and 5 (results available upon request) and thus we focus on the unweighted results in the paper

Table 1mdashSummary Statistics and Comparison to Other Polling and Online Data

mTurk sample CBS election poll American Life Panel(1) (2) (3)

Male 0428 0476 0417Age 3541 4899 4894White (non-Hispanic) 0778 0739 0676Black 00756 0116 0109Hispanic 00444 00983 0180Other racialethnic group 00759 00209 00410Employed (full or part) 0465 0587 0557Unemployed 0123 0104 0103Married 0397 0594 0608Has college degree 0433 0318 0309Voted for Obama 0675 0555 0559Political views conservatives (1) to liberals (3)

2176 1586

Observations 3741 808 1002

Notes This table displays summary statistics from our mTurk omnibus surveys in column 1 along with (weighted) averages based on a 2011 CBS news survey in column 2 and RANDrsquos online American Life Panel (ALP) in col-umn 3 We are grateful to Ray Fisman for providing us with summary statistics from the ALP

the control group Therefore a key concern is differential attrition between those assigned to the treatment versus control arms As the final row of Table 2 shows attrition is higher among the treatment group (20 percent versus 9 percent for the control group)19

Importantly however conditional on finishing the survey assignment to treatment appears randomly assigned That is while the treatment induces attrition overall it does not induce certain groups to differentially quit the survey more than others Table 3 shows the results from estimating (using the sample who complete the sur-vey) 14 separate regressions of the form Treatmen t ir = βCovariat e ir + δ r + ϵ ir where i indexes the individual r the survey rounds and δ r are survey-round fixed effects20 For each regression one of the control variables in Table 2 serves as Covariate Of the 14 regressions only two (for the black and Hispanic indicators) yield significant coefficients on the Covariate variable However given that their

19 For this comparison we can obviously only include individuals who remained in the survey long enough to have been assigned a treatment status The other comparisons in this table include all those who remained long enough to answer the given covariate question

20 We include round fixed effects δ r because in one round we assigned more than half the respondents to the treatment As such without round fixed effects Treatment becomes mechanically correlated to the characteristics of respondents in this round

Table 2mdashSummary Statistics for the Control Group Split by Liberals and Conservatives

Liberals Conservatives All(1) (2) (3)

Male 0407 0472 0422Age 32618 39823 35557White 0752 0838 0776Black 0090 0063 0085Hispanic 0039 0027 0037Asian 0090 0053 0078Married 0302 0543 0402Has college degree 0462 0455 0430Unemployed 0140 0076 0121Not in labor force 0093 0208 0144Voted for Obama in 2008 0914 0303 0674Inequality has increased 0836 0615 0738Inequality is a very serious problem 0414 0129 0285Top tax rate 34181 23996 30205Increase millionaire tax 0904 0452 0740Increase estate tax 0254 0080 0171Increase min wage 0822 0496 0690Support food stamps 0850 0446 0686Support EITC 0722 0418 0611Trust government 0171 0148 0158Scope of government is broad 3552 2349 3076Said would petition for higher income taxes (early rounds only)

0288 0118 0238

Send petition for high estate tax 0305 0141 0234Plan to vote Democrat 2012 0800 0182 0529Observations 821 475 1976

Notes This table displays summary statistics based on control respondents from the omnibus surveys stratified by self-reported liberal versus conservative status (on a five-point scale very liberal liberal moderate conservative very conservative) Column 1 is for liberals (less than 3 on the scale) while column 2 is for conservatives (more than 3 on the scale) Column 3 shows summary statistics for the entire control group including the ldquocenter of the roadrdquo respondents The complete wording of these survey questions is reported in the online Appendix

point-estimates have opposite signs it does not seem that say minorities systemat-ically attrit from the sample if they are assigned to the treatment

While we will control for these covariates as well as perform additional checks of attrition in the analysis that follows it is reassuring to see that con-ditional on finishing the survey there does not appear to be a discernible pattern in the types of respondents assigned to treatment We are quite fortunate in this regard as one might have expected that groups predisposed against reading about inequalitymdashperhaps conservatives or wealthier peoplemdashwould have been ldquoturned offrdquo by the treatment and differentially attritted The follow-up surveys discussed in Sections IV have essentially zero differential attrition by treatment status (see online Appendix Table 3) most likely because the treatments in the follow-up sur-veys are much shorter (making the treatment and control arms of the survey much closer in length)

III Results from the Omnibus Treatment

We present three sets of results First we analyze how the treatment affects respondentsrsquo answers to questions related to inequality per se not policies that might affect it Second we analyze specific policies eg raising taxes or increasing the minimum wage Third we analyze respondentsrsquo views about government as well as their political engagement

A Views on Inequality

Table 4 presents the effect of the omnibus treatment on questions related to inequality Odd-numbered columns do not include any controls outside of round

Table 3mdashAbility of Covariates to Predict Treatment Status Conditional on Finishing the Survey

Coefficient P-value

Voted for Obama in 2008 0003 0856Age minus0001 0479Liberal policy view 0002 0751Household income 0005 0109Married minus0013 0434Education minus0003 0575Male 0013 0447Black minus0066 0031Hispanic 0091 0021Native minus0043 0201Employed full time minus0012 0502Unemployed 0015 0539Not in labor force 0021 0376Student minus0027 0235

Notes For each row the coefficient and p -value are from regressions of the form Assigned to treatmen t ir = α + βCovariat e i + δ r + ϵ ir where Covariate is listed to the left in the row and δ r are survey round fixed effects Those tests are used to detect selective attri-tion (as treatment respondents are approximately ten percentage points less likely to complete the omnibus survey than are control respondents see online Appendix Table 3) If we regress treatment status jointly on all covariates and survey round fixed effects we obtain a p-value for joint significance of 012

fixed effects while even-numbered columns include standard controls (essentially those listed in Table 3)21

Column 1 of Table 4 shows that the treatment is associated with a 10-percent-age-point (or 36 percent) increase in the share agreeing that inequality is a ldquovery seri-ousrdquo problem Similarly dividing the point-estimate by the ldquopolitical gaprdquo (ie the liberal-conservative control group difference for the outcome variable) suggests that the treatment effect is equal to 36 percent of the political gap on this question (equal to 38 points in Table 2) While a convenient scaling dividing by the political gap is hardly a perfect metricmdashwhile political views are highly predictive of many of our outcomes this tendency varies and therefore some questions have larger political gaps than others We thus report both the absolute and scaled effects for all regressions Adding covariates in column 2 has no effect on the estimated treatment effect

The effects on the outcome ldquodid inequality increase since 1980rdquo are presented in columns 3 and 4 and are even larger both in absolute percentage points and when scaled by the political gap (54 percent of the conservative-liberal difference) likely because the informational treatment presented information directly related to the question

The effects on respondentsrsquo opinion of whether the rich are deserving of their income are presented in columns 5 and 6 They are statistically significant but markedly smaller in magnitudemdashequal to about 5 percentage points or one-sixth of the political gap Therefore it does not seem that treatment respondentsrsquo concern about inequality is being driven primarily by a vilification of the rich

In no case does the choice to exclude or include controls change the results (consis-tent with the results from Table 3 that conditional on finishing the survey there was little correlation between treatment status and standard covariates) Therefore to conserve space and reduce noise we show all results with covariates in the rest of the analysis

21 Specifically we include fixed effects for racialethnic categories employment status and state of residence indicator variables for voting for Barack Obama in 2008 being married gender and native-born status continuous controls for age and categorical variables for the liberal-to-conservative self-rating household income and education

Table 4mdashEffect of Omnibus Treatment on Opinions about Inequality (ldquoFirst-Stagerdquo outcomes)

Inequality very serious Inequality increased Rich deserving

(1) (2) (3) (4) (5) (6)

Treated 0102 0104 0119 0120 minus00500 minus00526[00154] [00144] [00130] [00128] [00119] [00114]

Control mean 0285 0285 0738 0738 0180 0180Scaled effect 0357 0365 0539 0540 0173 0182Covariates No Yes No Yes No YesObservations 3703 3703 3704 3704 3690 3690

Notes The three outcome variables are binary indicator variables coded as one if the respondent says that ldquoinequal-ity is a very serious problemrdquo ldquoinequality has increasedrdquo and ldquothe rich are deserving of their incomerdquo respectively All regressions have round fixed effects even those labeled as including ldquonordquo covariates Controls for covariates further include all variables in the randomization table (Table 3) plus state-of-residence fixed effects ldquoScaled effectrdquo is the coefficient on Treated divided by the difference between control group liberals and conservatives The row ldquoControl meanrdquo reports the mean of the outcome variable for the entire control group

Significant at the 1 percent level Significant at the 5 percent level Significant at the 10 percent level

Overall our omnibus treatment generated a very strong ldquofirst stagerdquo significantly shifting views about inequality and its increase in recent decades

B Views on Public Policy

Table 5 presents results for questions related to income and estate taxation The first two columns report results from the two questions on income taxationmdasha continuous variable asking respondents to choose an ideal average tax rate for the richest 1 percent and a categorical variable asking them whether taxes on million-aires should be raisedmdashshow statistically significant effects of the treatment in the ldquoexpectedrdquo direction22 However these magnitudes are small equal to about 10 percent of the liberal-conservative gap in both cases For example the treatment increases the preferred top 1 percent average tax rate by 093 percentage points whereas the gap between liberals and conservatives on this question is slightly over 10 percentage points (see Table 2) Hence we can rule out an effect on the tax rate for the top 1 percent larger than 20 percent of the liberal conservative gap

The omnibus treatment was hardly subtle in its discussion of income taxes focus-ing on how income growth might be shared more equitably through higher taxation and illustrating the temporal correlation between periods of high top tax rates and strong economic growth We also asked the income tax question in two different ways so the small magnitude of the results is unlikely to be an artifact of framing

By contrast there are very large effects for the estate tax (column 3 of Table 5) con-sistent with Sides (2011) The treatment triples the share of respondents supporting an increase in the estate tax and the effect size is more than double the liberal- conservative gap on this question We explore in the next section the reasons behind the large estate tax effects We show that both the informational and the emotional content of the estate

22 See online Appendix Figure 5 for the screen respondents used to choose their ideal tax rates

Table 5mdashEffect of Omnibus Treatment on Policy Preferences

Top rate $1M tax Estate Petition Min wage Trust Scope Dem 2012(1) (2) (3) (4) (5) (6) (7) (8)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

Control mean 3021 0740 0171 0234 0690 0158 3076 0529Scaled effect 00914 0111 2043 0394 00995 1250 0110 00246Observations 3741 3704 3673 3060 3690 3702 3704 3703

Notes ldquoTop raterdquo is continuous (respondentsrsquo preferred average tax rate (in percent) on the richest 1 percent) ldquoScoperdquo is also continuous (a 1ndash5 variable increasing in the preferred scope of government activities) All other vari-ables are binary ldquo$1M taxrdquo and ldquoEstaterdquo indicate the respondent wants income taxes on millionaires and the estate tax to increase respectively ldquoPetitionrdquo indicates she would write her Senator to increase the estate tax ldquoMin wagerdquo indicates support for increasing the minimum wage ldquoTrustrdquo indicates trust in government and ldquoDem 2012rdquo indicates the respondent plans to vote for the Democrat (Obama) in the 2012 presidential election ldquoCovariatesrdquo and ldquoscaled effectsrdquo are as specified in the notes to Table 4 The row ldquoControl meanrdquo reports the mean of the outcome variable in the control group All regressions in this and subsequent tables include control variables as defined in Table 4

tax treatment matter (a purely clinical information treatment with no emotional com-ponent increases support by 50 percent instead of more than doubling it)

A common critique of survey experiments that find large effects on opinion is that one cannot know how these effects impact actual behavior We try to partially bridge this gap by asking individuals whether they would send a petition to their US senator asking either to raise or lower the estate tax We provided a link to senatorsrsquo e-mails and also provided sample messages both for and against raising estate taxes We then asked if the respondent would send a petition for higher taxes a petition against higher taxes or nothing at all

We report these results in column 4 The treatment significantly increases the pro-pensity of respondents to say they would petition their US senator to raise the estate tax (though not surprisingly this effect is smaller than the pure opinion question suggesting attenuation from belief to action) Naturally we recognize that we must take respondentsrsquo word that they will send the e-mail and thus this outcome is not as concrete as for example knowing with certainty how they would vote in the next election At the very least this result confirms the strong effect of the treatment on views about the estate tax As mentioned we probe later on the robustness of this result and offer some thoughts on why it is so different from the income tax For now we merely note that these large results serve to dismiss a potential explanation of why the income tax results were so smallmdashthat there is something inherent in the mTurk experience that mutes respondentsrsquo policy responses

While so far we have focused on policies that affect the well-off we also asked a series of questions about policies that impact the bottom of the income distribution While the treatment induces significant but small (less than 10 percent of the politi-cal gap) effects for the minimum wage (column 5) it induces no significant increase in support for food stamps or the Earned Income Tax Credit (EITC) (results reported in online Appendix Table 4)23 The results thus suggest a contrast between direct transfer policies such as the EITC and food stamps and indirect transfer policies such as the minimum wage a theme that will also emerge in some of the follow-up work discussed in the next section24

C Views of Government and Political Involvement

Columns 6ndash8 of Table 5 reports results on the effect of the treatment on opinions about government The first question asked respondents ldquoHow much of the time do you think you can trust government in Washington to do what is rightrdquo and we code a respondent as trusting government if she answers ldquoalwaysrdquo or ldquomost of the timerdquo as opposed to ldquoonly some of the timerdquo and ldquoneverrdquo25 Column 6 reports a large decrease in the share of treatment respondents agreeing that the government can be trusted The treatment is equal to the entire liberal-conservative gap but operates

23 In later follow-up work we asked a small pilot group to write open-ended responses to many of our outcome variables Many respondents had little familiarity with the EITC (though we always provided a description) so the non-result for that outcome might need to be interpreted more cautiously No respondent indicated unfamiliarity with food stamps or the minimum wage however

24 There are other possible distinctions between these policies For example respondents may have stronger racial stereotypes of food-stamp recipients than they do of minimum-wage workers

25 This question is taken from the American National Election Studies (ANES) httpwwwelectionstudiesorgnesguidetoptabletab5a_1htm (accessed December 1 2014)

in the opposite direction to the other outcomes in that it makes respondents take the more conservativemdashand less trustingmdashview on this question26 Note also that consistent with the trends noted in the introduction the control group has a very low level of trust in governmentmdashonly about 16 percent are trusting of government by our definitionmdashand that the contrast of liberals and conservatives about trusting government is fairly small (17 versus 145 percent see Table 2) The low baseline level of trust in the control group suggests that the treatment effect we observe might in fact understate the true effect experienced by the treatment group as their ability to express an even lower opinion of government is limited by floor effects

The second question assesses respondentsrsquo preferred scope of government ldquoNext think more broadly about the purpose of government Where would you rate yourself on a scale of 1 to 5 where 1 means you think the government should do only those things necessary to provide the most basic government functions and 5 means you think the government should take active steps in every area it can to try and improve the lives of its citizensrdquo27 Intriguingly the treatment significantly moves people toward wanting a more active government (column 7 of Table 5) Providing information about the growth of inequality and the ability of the govern-ment to raise taxes and redistribute have complicated effects on views of govern-ment It appears to make respondents see more areas of society where government intervention may be needed but simultaneously make them trust government less We return to these results linking trust in government to preferences on government scope in Section IV

Finally as shown in column 8 the treatment has almost no effect on respon-dentsrsquo planned voting choice for the 2012 presidential elections (recall that the omnibus-treatment surveys were completed before the November 2012 election) There is at best a marginal effect in the direction of supporting President Obama This result is consistent with the relatively mild policy effects overall The treatment may simultaneously make individuals want the more redistributive policies of the Democratic party and distrust the party in power (the Democrats under Obama at least in the executive branch and the Senate)28

D Robustness Checks

Persistence of EffectsmdashBefore mTurk recontacting survey respondents was onerous and thus few papers were able to test the duration of effects from informa-tional survey experiments None of the papers cited in the introduction on the effect of information on redistributive preferences follows up with respondents to measure the duration of the effects29

26 We say that being less trusting of government is the ldquoconservativerdquo view because in our data as well as GSS data from the same time period conservatives indeed report lower trust in government These tendencies are sen-sitive to the party in power (eg in the GSS during the George W Bush administration conservatives were more trusting of the executive branch than were liberals)

27 This question comes from Gallup28 In the interest of space there are some outcome variables we relegate to the online Appendix The full set of

all results from the omnibus survey are found in online Appendix Tables 4 5 6 29 In their review of the use of survey experiments Gaines Kuklinski and Quirk (2007) name measuring dura-

tion effects as their top recommendation for future work in the area

The evidence from the few papers that do test persistence is not encouraging Luskin Fishkin and Jowell (2002) find that even the immediate effects of an extreme interventionmdashin which British participants spent a weekend with experts with the goal of debunking misconceptions about crime and prison policymdashdo not persist ten months later Indeed in a similarly intense intervention focused on issues related to campaign finance Druckman and Nelson (2003) find that their results dissipate within ten days While not a survey experiment per se Gerber et al (2011) use variation in the location of campaign television advertising to show that per-suasive effects are strong the week the ad airs but have little persistence beyond the first week Perhaps closest to our methodology Lecheler and Vreese (2011) sample Dutch respondents to test for the effect of informational treatments on opinions about economic aid to Bulgaria and Romania while the treatment effect persisted after one week it was insignificant after two

The flexibility of the mTurk platform offers the possibility of resurveying partici-pants months after the original survey In the third round of the omnibus survey we attempted to recontact respondents one month after taking the survey Out of 1039 respondents who completed the original survey 145 (14 percent) completed the follow-up survey The follow-up survey asked most of the outcome questions in the original survey but did not include the informational treatment

With a relatively low take-up rate a concern is that follow-up respondents are differentially selected Online Appendix Table 7 suggests that while some selec-tion takes place (by age marital status and employment status) the most important variables in terms of predicting preferences (support of Obama and overall liberal-versus- conservative policy views) show no differential selection into the follow-up sample Nor does initial treatment status predict take-up and thus we have a roughly equal number of control and treatment observations in the follow-up sample

We compare the original results for these 145 observations to their responses one month later for selected outcomes in Table 6 and for all other outcomes in online Appendix Tables 8 and 9 As only some outcomes show a substantial initial treat-ment effect for the N = 145 subsample it is not feasible to have meaningful tests of persistence for all outcomes

Columns 1 and 2 show that our most robust outcome result from the original sur-veymdashsupport for increasing the estate taxmdashis strongly persistent In absolute terms 58 percent of the effect size remains one month later more than doubling the share who support the policy And the effect one month later remains highly statistically significant

Columns 3 and 4 show similarly strong results for views on the proper scope of government The follow-up result in column 4 actually shows an increase in the point-estimate though it is within the confidence interval of the result in column 3

Columns 5 and 6 show that the initial treatment effect on ldquotrust in governmentrdquo is slightly larger than for the full sample with a negative but now insignificant effect persisting one month later

Unfortunately as columns 7 and 8 show one of the main outcome variables from the omnibus surveymdashconcern for inequalitymdashyields an initial treatment effect of essentially zero for the subsample and thus testing for persistence is not partic-ularly meaningful Given that our initial treatment often had small effects for the entire sample it is not surprising that only some outcomes yield substantial initial

treatment effects for the subsample We thus relegate the follow-up results for all these outcomes to online Appendix Tables 8 and 9

Overall the follow-up analysis shows once again that the estate tax emerges as the policy most robustly and significantly affected by our omnibus treatment

Bounding the Effects of Differential AttritionmdashWhile we showed in Table 3 that conditional on finishing the survey assignment to the treatment appears as good as random here we further probe the potential effects of attrition To conduct a bound-ing exercise we assume either that (i) attriters would have all had the average ldquolib-eralrdquo view for each outcome or (ii) they would have had the average ldquoconservativerdquo view for each outcome Given that attrition does not actually vary by political views (see online Appendix Table 2) but outcome values vary substantially by political views (see Table 2) this test should provide generous upper bounds on the potential effects of attrition The results in online Appendix Table 10 shows that no signs flip for any of our main outcome variables under either the conservative (columns labeled ldquoCrdquo) or liberal (columns labeled ldquoLrdquo) attrition assumptions

Next we examine how the level of differential attrition affects our results do our results only hold in survey rounds with high differential attrition between the control and treatment group The first three rounds of the omnibus surveys had very similar differential attrition rates (between 12 and 16 percent) whereas the fourth had a substantially lower attrition rate (5 percent) Online Appendix Tables 11 and 12 show that our main results on concern for inequality support for the estate tax and trust in government are robust and at times stronger for the low-differen-tial-attrition round the round where we expect our identification assumptions to be most robust As before the ldquonon-resultsrdquo for other outcomes remain (not shown)30 In Section IV we analyze follow-up surveys where the treatment is much shorter and where there is virtually no differential attrition by treatment status (see online

30 In our context the only observable variable that is correlated with differential attrition between control and treatment is the round of the experiment Hence our comparison across rounds is the simplest and most transparent nonparametric form of DiNardo-Fortin-Lemieux (DFL) reweighting

Table 6mdashResults from the Follow-Up Survey One Month Later

Increaseestate tax

Governmentscope

Trust government

Inequality very serious

First Follow-up First Follow-up First Follow-up First Follow-up(1) (2) (3) (4) (5) (6) (7) (8)

Treated 0337 0195 0259 0364 minus0122 minus00691 000833 0102[00953] [00910] [0207] [0200] [00611] [00582] [00809] [00770]

Control mean 0180 0179 2995 2910 0122 0128 0283 0218Observations 145 145 145 145 145 145 145 145

Notes All outcomes and terms are as defined in Tables 4 and 5 For each dependent variable column ldquoFirstrdquo is the result from the first survey while column ldquoFollow-uprdquo is the result from the follow-up survey one month after the initial survey We use a more limited set of control variables given the small sample size All regressions are run on the subsample of respondents who entirely completed the follow up survey

Appendix Table 3) The fact that these follow-up surveys largely confirm our omni-bus treatment results provides further reassurance that differential attrition is not driving our results

Robustness Across RoundsmdashAs our rounds took place at different dates with dif-ferent stories dominating the news cycle we might worry that the treatment effects are being driven by a single round We verified that dropping rounds one by one does not change the sign or significance of the main results

Survey FatiguemdashFinally ldquosurvey fatiguerdquo would not seem to explain our results For example the question ldquois inequality a serious problemrdquo comes before top tax rates which precedes the estate tax question our strongest effect Therefore there is no monotonic relationship between the strength of the treatment effect and the order of the outcome variables

Experimenter Demand EffectsmdashA potential bias that is more difficult to measure is differential experimenter demand effectsmdashperhaps it is the case that a variable such as ldquoinequality is a serious problemrdquo is more susceptible to demand effects than concrete policy questions such as ldquopreferred top income tax ratesrdquo An indirect test is to examine gender differences by outcome variable as women appear more likely to give the ldquodesiredrdquo answer (see eg Bernardi 2006 Dalton and Ortegren 2011 and citations therein) We find very small gender differences overall and no pattern whereby they are larger for women for the ldquofirst-stagerdquo outcomes (results available upon request) Recent work argues that demand effects are likely muted with Internet surveys (see eg Kreuter Presser and Tourangeau 2008 and Gelder Bretveld and Roeleveld 2010)

IV Understanding Our Results with Follow-up Surveys

The follow-up surveys share the following structure While we repeated most of the outcome questions used in the omnibus surveys there are some differences (based on input from referees and others) For example we ask respondents to report whether ldquopoverty is a serious problemrdquo as well as rank ldquoprivate charityrdquo and ldquoeducationrdquo in a list of tools to address inequality (so as to gauge whether respon-dents react to the treatments by turning to optionsmdashsome nongovernmentalmdashmore often advocated by political conservatives)31 We also replace the question about the EITC (which we feared might not be sufficiently familiar to respondents) with a general question about ldquoaid to the poorrdquo and a specific question about public hous-ing while retaining the minimum wage and food stamp questions

For the sake of completeness we used the same battery of outcome questions for all follow-up surveys even when certain follow-up treatments were unlikely to affect a given outcome For the sake of brevity and exposition we only discuss in the main text those outcomes that are relevant to a given treatment but all other

31 For example Mccall and Kenworthy (2009) argue that Americans care about inequality but prefer policy levers such as education to combat it not income redistribution In our data (control group) conservatives are indeed more likely to rank education and private charity above tools that more directly involve government redistribution

outcomes are reported in the online Appendix for each treatment Importantly in this section we use data solely from the follow-up surveys because the control groups in the omnibus survey and the follow-up surveys are not directly comparable and because the wording of some of the questions has changed

Section A explores why the estate tax appears to be an anomaly first verifying that the effect is robust to changes in presentation and then measuring the pure infor-mational impact of our treatment Section B explores potential mechanisms for why most other policies are more impervious to informational interventions

A Why Are Views about the Estate Tax So Elastic to Information

In this section we present two types of follow-up analysis on the estate tax First we verify whether the estate tax treatment effectmdashan outlier among the policy out-comes analyzed in the previous sectionmdashis truly robust After showing that it with-stands several significant modifications of the treatment we then present evidence as to why this effect is so strong Our view is that misinformation about the estate tax is far greater than for the other policies we surveyed such that the informational treatment has an especially large impact32

Verifying the Large Estate Tax EffectsmdashRecall that the omnibus treatment includes not only information about the incidence of the estate tax but several other components as well (eg the interactive feature showing respondentsrsquo place in the income distribution among the others we described in Section I) To gauge the sensitivity of the estate tax effect to this additional information we redid the experi-ment with a treatment that only included the slide on the estate tax Furthermore the original estate tax treatment shows a picture of a mansion and notes that the estate tax can help ldquolevel the playing fieldrdquo (see online Appendix Figure 4) We thus for-mulated a treatment that decreased the emotional impact of the estate tax treatment and that only mentions the incidence in dry factual terms (see online Appendix Figure 6) We call the first version the ldquoemotional estate tax treatmentrdquo and the sec-ond the ldquoneutral estate tax treatmentrdquo Again neither of these treatments contains the other non-estate-tax components of the omnibus treatment

Table 7 displays results for the key outcome variables In contrast to the omni-bus treatment the ldquoemotionalrdquo estate tax treatment has no effect on views about whether inequality is a problem whether it has increased or whether the rich are ldquodeservingrdquo (columns 1 2 and 3) The ldquoneutralrdquo treatment appears to have counter-vailing effects increasing concern for inequality (though this effect is much smaller than that of the omnibus treatment) while decreasing the sense that inequality has increased These much weaker effects are not surprising because these two treat-ments provide no information about income inequality or its trends

However column 4 shows that the effect of even these more limited treatments on opinions about the estate tax remains strong The point estimate for the ldquoemotional

32 Theoretically the prospect for upward mobility mechanism of Beacutenabou and Ok (2001) that limits the desire for redistribution might become irrelevant when respondents realize that only 1 decedent out of 1000 pays the estate tax Following Alesina and Angeletosrsquos (2005) theory respondents might also support the estate tax on the very wealthy as they realize that receiving a very large inheritance is due entirely to luck and not effort of the inheritor

treatmentrdquo is nearly as large as that of the omnibus treatment (0289 versus 0357) The ldquoneutralrdquo effect is smaller (0109) though both in absolute and scaled terms swamps any policy effect (excluding the estate tax itself) associated with the omni-bus treatment Recall that the omnibus treatment provided extensive interactive and personalized information on income inequality and income tax rates and typically produced scaled effects on the income tax outcomes of 10 percent The ldquoneutralrdquo estate tax treatment consisted of a total of four sentences but nonetheless produced a scaled effect on the estate tax four times as large (408 percent of the liberal- conservative gap) This stark contrast highlights how much more elastic to infor-mation views about the estate tax are than those about the income tax and other policies

As shown in column 5 both treatments make respondents more likely to say they will petition their senator (scaled effects greater than 02) but this effect is not statistically significant The significant effect with the omnibus treatment suggests that the background information on growing inequality might be required to induce more respondents to connect their policy views with political activism Column 6 shows that the effect on trust in government is negative (as in the omnibus treat-ment) but not significant33

Why are Estate Tax Preferences So Malleable to Informationmdash At first we attributed this finding to our treatment having larger effects for topics that held lit-tle ex ante salience for our respondents However recent polling data suggests the

33 Given that the omnibus treatment had at best small effects on income tax and transfer policies it is not sur-prising that the estate-tax-only treatments do not produce consistently significant effects on these outcomes either (online Appendix Table 13 and 14)

Table 7mdashResults from the Estate Tax Survey

Inequality increased Deserving

Estatetax Petition Trust

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

Treated (emotional) 00381 minus000239 minus00247 0289 00313 minus00164 0316[00258] [00243] [00206] [00258] [00208] [00205] [00263]

Treated (neutral) 00511 minus00501 minus00244 0109 00239 minus000558 0375[00259] [00244] [00206] [00259] [00209] [00205] [00264]

Control mean 0307 0771 0174 0210 0132 0153 0120Scaled emotional effect 0118 0011 0098 1085 0265 0235 3386Scaled neutral effect 0159 0223 0097 0408 0202 0080 4014p-value 0612 0049 0991 0000 0722 0598 0026Observations 1777 1777 1777 1777 1762 1756 1773

Notes The ldquoemotionalrdquo treatment repeats the estate tax slide from the omnibus treatment but eliminates the rest of the treatment The ldquoneutralrdquo treatment is a version of the ldquoemotionalrdquo treatment that attempts to remove any fram-ing effects or emotional appeals to focus solely on the information The outcomes in columns 1ndash6 are as defined in Tables 4 and 5 (ldquoDeservingrdquo is the abbreviation for ldquothe rich are deserving of their incomerdquo) ldquoEstate tax corrrdquo indicates that the respondent chose the correct multiple-choice outcome for a question asking what share of people who die are subject to the estate tax p-value is the p-value of the test that the coefficients on the treated ldquoemotionalrdquo and the treated ldquoneutralrdquo are the same

estate tax is very salient to respondentsmdashin 2010 Gallup respondents named avert-ing an increase in the estate tax as their top priority for the lame-duck session of Congress above extending unemployment benefits and the Bush income tax cuts34 Moreover there were no more ldquomissingrdquo responses on the estate tax question than on other policy questions in the control group further evidence that the estate tax is not an obscure issue to respondents in our sample

A more promising explanation is that while respondents may view the estate tax as a salient issue they may hold misinformed views on the topic Indeed as documented by Slemrod (2006) 82 percent of respondents favor estate tax repeal but 49 percent of respondents believe that most families have to pay it compared to 31 percent who believe only a few families have to pay and 20 percent who admit to not knowing In contrast the public appears much better informed about policies such as the minimum wage or the individual income tax35 As a result providing basic information on how the current federal estate tax is limited to the very wealth-iest families might serve as a large informational shock

We directly tested this hypothesis by adding a question on the incidence of the estate tax to the follow-up surveys Respondents were asked to choose the share of decedents subject to the estate tax from among the following percentage options less then 1 1 10 20 40 60 and 100 percent If anything the greater detail offered for choices below 20 percent would seem to tip off respondents that the answer is a small number but only 12 percent of control group respondents answered cor-rectly (random guessing would be correct 14 percent of the time) and accuracy varied substantially by political orientation (16 percent of liberals versus 6 percent of conservatives)

Column 7 of Table 7 shows the effect of the two estate tax treatments on respon-dentsrsquo likelihood to choose the correct response Both treatments roughly triple the likelihood of answering correctly strongly suggesting that information is a key mechanism behind the large effects of the omnibus treatment36 Importantly misin-formation is not a sufficient condition for an informational treatment to have large effects As noted earlier Kuklinski et al (2003) found that correcting substantially misinformed views on welfare was not sufficient to change respondentsrsquo support though perhaps the lack of elasticity is due to the racial stereotypes the world ldquowel-farerdquo brings to mind (Gilens 1996) The estate tax may be one of a few issues on which voters are highly misinformed but their ignorance is not linked to racial or other stereotypes In any case extrapolating from the estate tax effects would give vastly biased views of the ability of information to move other redistributive policy preferences as we saw in the previous section and as we further document below

34 See httpwwwgallupcompoll144899Tax-Issues-Rank-Top-Priority-Lame-Duck-Congressaspx (accessed December 1 2014)

35 A recent Pew survey shows that 73 percent of respondents could identify the correct current minimum wage (see httpwwwpeople-pressorg20141002from-isis-to-unemployment-what-do-americans-know) (accessed Decem-ber 1 2014) For the individual income tax we asked respondents in an earlier pilot to give us their best guess of actual average tax rates by income brackets On average respondents came fairly close to actual tax rates both in level and in terms of progressivity For example for top bracket taxpayers with income above $379150 they guessed a tax rate of 291 percent on average when the actual tax rate based on 2012 IRS statistics is 264 percent Consistent with these results Fujii and Hawley (1988) find that on average survey respondents perceive fairly accurately the marginal tax rates they face

36 Our results offer experimental support for the observational regression analysis presented by Slemrod (2006) none showing that support for the estate tax is lower when respondents believe that most families have to pay it

B Exploring the Limited Treatment Effects on Policy Preferences

We explore three potential explanations for why the omnibus treatment had small policy-preference effects (aside from the estate tax) Of course other explanations may exist so one should not view our analysis of the mechanisms behind the policy ldquonon-resultsrdquo as definitive or exhaustive

Does Government Distrust Explain Limited Treatment EffectsmdashAs documented in Section III the omnibus treatment significantly reduces trust in government It is perhaps not surprising that an informational treatment emphasizing a dramatic increase in income inequality would lower respondentsrsquo view of government But to our knowledge it remains an open question whether lowering trust in government has a causal effect on policy preferences This question has perhaps never been more relevant in the US context given that Americansrsquo trust in government is at histori-cally low levels as noted in the introduction

To test the causal effect of trust in government on policy preferences we devised a treatment that lowers trust but does not affect views on other factors that might affect policy preferences This task is not easymdashas we saw with the omnibus treatment information about inequality reduces trust in government but also increases concern about inequality meaning the omnibus treatment effects on the policy outcomes are the joint effect of increasing concern about inequality (which we hypothesize would increase support for government action) and reducing trust in government (which we hypothesize would decrease it)

We began by collecting a small pilot study ( N asymp 150 ) on mTurk where we asked people to answer our basic trust question (how often they can trust the government to do what is right) but then to explain why they answered the way they did Note that they answer this question directly after answering the demographic questions and are thus not being primed to think about inequality There is no ldquotreatmentrdquo in this pilotmdashwe are merely asking people to explain their opinion The pilot group cast light into why trust in government is currently so low Respondents feel politicians are out to enrich themselves and their wealthiest donors ldquoMoneyrdquo ldquocorporationsrdquo and ldquospecial interestsrdquo are some of the most commonly used words and phrases in these answers as online Appendix Figure 7 shows The detailed descriptions given by respondents allowed us to develop primes we thought could lower trust in gov-ernment without necessarily affecting other factors that would have a direct effect on policy preferences

Our treatment consists of several multiple-choice questions that induce respon-dents to reflect on aspects of government they dislike For example we asked if they agree that ldquoPoliticians in Washington work to enrich themselves and their largest contributors instead of working for the benefit of the majority of citizensrdquo (90 per-cent do) We also showed them results from a ranking of OECD countries in terms of government transparency in which the United States was categorized in the bottom quartile (see online Appendix Figure 8 for a screenshot and online Appendix A for the full description)

ResultsmdashTable 8 shows the results of this treatment on a variety of outcomes Column 1 shows that the first stage ldquoworksrdquomdashthe treatment significantly decreases

respondentsrsquo stated trust in government by 58 percentage points in absolute terms or 178 times the liberal-conservative gap on this question This effect is slightly larger than the effect of the omnibus treatment (roughly 11 times the liberal- conservative gap) not surprising given that the goal of this treatment was to lower trust As we saw with the omnibus treatment respondents appear to separate how much they trust the government with what they view as its proper scope as the treatment has no effect on that outcome (column 2) The treatment makes them more likely to view the government as wasteful but the effect is not significant (column 3)

Columns 4ndash6 suggest that we were largely successful in devising a treatment that isolates the effect of trust at least with respect to our standard questions on income inequality and poverty There is a marginal effect of the treatment in increasing con-cern about inequality but no effect on the sense inequality has increased or the sense that poverty is a problem The results from the omnibus treatment suggest that if anything the uptick in concern about inequality should have a mildly positive effect on treatment respondentsrsquo tendency to support redistributive policies As such it would mask the effects of decreasing trust in government on support for redistribu-tive policies which we hypothesize to be negative

Table 9 displays those results The treatment decreases support for a tax on mil-lionaires though this result is not quite statistically significant (when the continuous top tax rate is used instead as the outcome the coefficient is positive but essentially zero see online Appendix Tables 15 and 16 for this and other results not discussed in the main text) While stated support for expanding the estate tax is essentially unchanged by the treatment the stated willingness to petition for its expansion is significantly reduced (a scaled effect of 0588)

The estimated effects of trust on support for transfer programs to the poor are much less equivocal While support for the minimum wage is unaffected (col-umn 4) treatment respondents significantly reduce their support for ldquoaid to the poorrdquo generally (column 5) and food stamps and public housing specifically (col-umns 6 and 7) Finally some interesting results emerge when respondents are asked to rank a list of options for addressing inequality (a higher number here means more

Table 8mdashEffect of Negative Trust Prime on ldquoFirst-Stagerdquo Variables

Trust Scope EfficientInequality very

seriousInequalityincreased

Poverty versus serious

(1) (2) (3) (4) (5) (6)

Treated minus00582 00236 minus00278 00547 00119 minus000257[00203] [00688] [00346] [00311] [00289] [00313]

Control mean 0125 3031 1423 0343 0755 0383Scaled trust effect 1730 00170 0109 0182 0341 000828Observations 899 899 898 899 899 899

Notes The negative trust prime treatment consists of several multiple-choice questions that made respondents reflect on aspects of government they dislike For outcomes ldquoEfficientrdquo is taken from a 1ndash3 scale of how much respondents think the government wastes money (we ldquofliprdquo it so that it is increasing with perceived government effi-ciency) ldquoPoverty very seriousrdquo is an indicator variable for whether the respondent views poverty as a very serious problem All other outcomes are as defined previously

support) Column 8 shows the treatment causes respondents to elevate a nongovern-mental solution to inequalitymdashprivate charity which as noted at the beginning of the Section is generally preferred by more conservative respondents

DiscussionmdashDecreasing respondentsrsquo trust in government appears to have a strong negative effect on support for direct government transfers As further sup-port for the trust mechanism the treatment has no effect on support for the min-imum wage which is an indirect transfer that does not involve the government receiving and redistributing tax dollars Recall also that the omnibus treatment failed to increase support for direct transfer programs (the EITC and food stamps) but did increase support for the minimum wage As Table 9 shows that support for the minimum wage appears unaffected by changes in trust trust emerges as a plausible mediating variable that can explain the pattern of results for the omnibus treatment

Emotional versus Factual AppealsmdashThere is a long psychology literature that suggests that for many issues emotional appeals produce larger changes in atti-tudes than more factual presentations37 Indeed the estate tax follow-up experiment described in Section IVA showed that the neutral treatment had a smaller effect than the emotional treatment While our omnibus treatment provided extensive interac-tive and personalized information it was mostly numeric in nature which may have limited its ability to move policy preferences Similarly the focus on the ldquotop 1 percentrdquo might be less effective than focusing more intensely on the bottom of the distribution

To test this idea we developed a treatment meant to create empathy between the respondent and low income families Again the treatment was personalized and interactive For example we asked respondents to ldquo[t]hink about a family of X 1 with X 2 parent(s) working full timehellipand X 3 kidshellipWhat would be the minimal monthly expenses that such a family would have to make to afford living where you liverdquo

37 See eg Edwards (1990) Rosselli Skelly and Mackie (1995) Loef Antonides and Raaij (2001) Huddy and Gunnthorsdottir (2000) and citations therein

Table 9mdashEffect of Negative Trust Prime on Outcome Variables

$1M tax Estate tax Petition Min wage Aid poor Food stamps Housing Private charity(1) (2) (3) (4) (5) (6) (7) (8)

Treated minus00421 minus000168 minus00602 minus000428 minus0139 minus0153 minus0163 0187[00275] [00266] [00236] [00902] [00616] [00673] [00614] [00791]

Control mean 0722 0204 0174 2673 2675 2454 2581 1800Scaled trust effect 00949 000728 0580 000531 0128 0119 0133 0169Observations 899 895 899 899 899 899 899 850

Notes The negative trust prime treatment consists of several multiple-choice questions that made respondents reflect on aspects of government they dislike Outcome variables are defined as follows ldquoMin wagerdquo is a 0ndash4 categorical variable increasing in sup-port for the minimum wage (0 indicates most opposition and 4 indicates most support) ldquoFood stampsrdquo is a 0ndash4 categorical vari-able increasing in support for food stamps ldquoAid poorrdquo is a 0ndash4 categorical variable increasing in support for programs that aid poor households ldquoHousingrdquo is a 0ndash4 categorical variable increasing in support for funding public housing programs ldquoPrivate charityrdquo is an indicator of where (among a list of five policy approaches) the respondent puts ldquoprivate charityrdquo as a preferred method for addressing inequality (the variable increases with relative support for private charity) All other outcomes are as defined previously

The values X 1 X 2 and X 3 were interactively matched to the household composition that the respondent earlier gave in the demographic module at the start of the survey The respondent then entered dollar amounts for monthly rent utilities transporta-tion food and expenses related to children We then showed them how the budget they devised compared with the income at the poverty line (based on the respon-dentsrsquo household size) emphasizing to them that the budget did not even include items such as health care clothing furniture and costs related to schooling (see the online Appendix for a complete description of the treatment and online Appendix Figure 9 for a screenshot)38 The slides with this information also included photos of low income families

ResultsmdashOverall the results track very closely to those from the original omni-bus treatment We obtain large ldquofirst-stagerdquo effects on concern for poverty and inequality but little movement on policy preferences

Table 10 presents the key outcomes The treatment has significant effects on con-cern about inequality (column 1) and not surprisingly large effects on whether poverty is a serious problem (equal to over 30 percent of the political gap for this outcome)39 However just like the omnibus treatment this follow-up ldquoemotionalrdquo treatment has limited effect on policy preferences Of the four poverty-policy ques-tions we asked only two exhibit a marginally significant treatment effect (food stamps and aid to the poor and even then just below 8 percent of the political gap) Similar to the omnibus treatment this follow-up treatment reduces trust in govern-ment though the effect is smaller and not significant40

38 The large majority (76 percent) devise a budget in excess of the income at the poverty line for a household of their type

39 As detailed in online Appendix Table 17 the treatment increased the likelihood of correctly choosing the actual poverty rate from multiple choices though because many control respondents overestimated the poverty rate it did not on net increase their estimate of the poverty rate The fact that the treatment had such a large effect on perceiving poverty as a ldquovery serious problemrdquo likely works through the intensive margin perhaps through the creation of empathy the treatment highlights how difficult it would be to manage with limited income

40 The treatment had very small but positive effects on taxes on the well-off always well below 10 percent of the political gap and not significant See online Appendix Tables 17 and 18 for these and all other outcomes not displayed in Table 10

Table 10mdashEffect of ldquoEmotionalrdquo Treatment on Outcome Variables

Inequality increased

Poverty very serious

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

Control mean 0337 0775 0296 2546 2559 1832 2539 0124Scaled poverty effect 0221 0225 0257 00449 00714 00866 00291 00931Observation 1002 1001 799 799 799 799 799 1002

Notes The ldquoemotionalrdquo treatment aimed at creating empathy between the respondent and families living in poverty Respondents were told about poverty rates and filled out a minimum budget for a family like theirs living in the same city Respondents were then shown how their minimum budget compared to the poverty line All outcomes are as defined previously ldquoMin wagerdquo ldquoAid poorrdquo ldquoFood stampsrdquo ldquoHousingrdquo are all categorical 0ndash4 and increasing in support as in Table 9 The lower number of observations in col-umns 3ndash7 is due to the fact that these questions were not asked in one smaller wave (sample of 200)

DiscussionmdashAs readers can verify by taking the surveys themselves the omni-bus treatment and this ldquoemotionalrdquo follow-up are very different in spirit The omni-bus treatment focused largely on the top 1 percent and was more factual in nature whereas the follow-up treatment focused on the disadvantaged and sought to create empathy both with our ldquoput yourselves in their shoesrdquo exercise as well as photo-graphs of low income families

Despite these stark differences the results are very similar It is relatively easy for treatments to affect how much individuals are ldquoconcernedrdquo with any issue but much harder to increase their support for policies that would seem directly related to addressing said issues Our final follow-up survey attempts to make the connection to policy measures more explicit

Connecting ldquoConcernsrdquo with Policy MeasuresmdashBartels (2005 p 16) docu-ments the seemingly odd result that even though the individuals in his 2002 sample were worried about inequality and aware that the tax cuts proposed by the Bush administration in 2001 favored the wealthy they still supported them by a large mar-gin He concludes that ldquoAmericans support tax cuts not because they are indifferent to economic inequality but because they largely fail to connect inequality and pub-lic policyrdquo

We directly test this notionmdashthat respondents do not connect their ldquoconcernsrdquo with policies meant to address themmdashin our final follow-up survey In this version we largely repeat the low income ldquoemotionalrdquo treatment described in Section IIB but also add slides showing how current government programs help these households First after entering in the expenses in the budget exercise the treatment describes a family earning one full-time full-year minimum-wage income making a salient connection between the level of the minimum wage and family income at the bot-tom of the income distribution Second respondents are told that ldquoThe food stamps program helps many low income families such as those earning only one minimum wage It provides $150month per person to help with food expensesrdquo Hence the connection between poverty and a government program is made explicit Online Appendix Figure 10 provides a screenshot

ResultsmdashWe repeat the results for the key outcome variables in Table 11 The ldquofirst-stagerdquo effects of this treatment are smaller and not significant It is not surpris-ing that we do not see much movement in variables related to inequality since the treatment did not provide any direct information on the topic Despite the focus on the situation of a low income household treatment respondents do not view poverty as a more serious problem We speculate that emphasizing the efficacy of a govern-ment poverty program might have the effect of making poverty and inequality seem less severe

Despite the somewhat smaller first-stage effects the effects on our policy out-comes are consistently positive and significant Support rises for the minimum wage (column 3) aid to the poor (column 4) food stamps (column 5) and public housing (column 6) The effect on ldquoaid to the poorrdquo is positive but not significant It should be noted however that with the exception of the minimum wage these effects are still relatively small (roughly about 10ndash15 percent of the political gap) It is also the case that the treatment does not consistently increase support for actually sending

money to Washington to pay for these policies the effects on income and estate taxes for the well-off are mixed (see online Appendix Tables 19 and 20)

However it does appear that the interaction of the empathic portrayal of low income families along with information emphasizing the efficacy of a transfer program has a meaningful effect on the policies respondents support Column 7 suggests that in contrast to the trust treatment this treatment reduces the relative attractiveness of the nongovernmental solution to inequality private charity Finally column 8 shows that there is no significant effect of the treatment on trust in govern-ment though the point estimate is negative

DiscussionmdashWhile this treatment indeed moved policy preferences it is worth noting its highly explicit nature After completing an exercise where they contem-plated the budget constraints of a low income family respondents were shown in concrete terms how a government program helps such a household make ends meet Even then while support for many poverty-related programs significantly increased the largest effect remains the minimum wage an indirect transfer pro-gram Moreover the treatment does not have a consistent effect in terms of inducing treatment participants to desire higher taxes (even if only on the wealthy) to pay for these programs

Taken together the results from these three follow-up surveys suggest the diffi-culty in moving most policy preferences While concern for an issue is highly elastic to information translating this concern into a change in policy preference appears very difficult with the consistent exception of the estate tax

V Conclusion

The standard median-voter model predicts that support for redistribution should increase with income inequality yet there has been little evidence of greater demand for redistribution over the past 30 years in the United Statesmdashdespite his-toric increases in income concentration A possible explanation is that people are unaware of the increase in inequality such that greater information would substan-tially move redistributive preferences We gather over 10000 observations using

Table 11mdashEffect of Policy Treatment on Outcome Variables

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Policy treatment 00405 minus000637 0323 0133 0313 0176 minus0137 minus00325[00279] [00272] [00949] [00638] [00970] [00636] [00709] [00207]

Control mean 0343 0326 2546 2559 1832 2539 2025 0149Scaled policy effect 0108 00196 0310 00811 0153 0129 00740 0654Observations 1111 1111 806 806 806 806 1068 1111

Notes The policy treatment aimed at creating empathy between the respondent and families living on a minimum wage Respondents filled out a minimum budget for a family like theirs living in the same city Respondents were then shown how their minimum bud-get compared to the minimum wage and how food stamps add $150 per personmonth to the budget of such a family All outcomes are as defined previously ldquoMin wagerdquo ldquoAid poorrdquo ldquoFood stampsrdquo ldquoHousingrdquo are all categorical 0ndash4 and increasing in support as in Table 9 The lower number of observations in columns 3ndash7 is due to the fact that these questions were not asked in one smaller wave (sample of 300)

Amazonrsquos Mechanical Turk to conduct a series of survey experiments to extensively explore this hypothesis

Our results suggest that generally greater information can increase respondentsrsquo sense of concern about an issue but not necessarily their support for policies that might ameliorate it Information about income inequality and poverty has only a limited (and typically statistically insignificant) tendency to increase support for higher income taxes on the well-off or transfer programs for the disadvantaged

We present evidence that extreme distrust of government appears to explain part of this null effect First trust in government is very low in our sample as it cur-rently is among Americans more generally Second many of our treatments appear to further reduce this already low level of trust Third and most novel relative to the literature we show that decreasing trust has a causal effect on diminishing sup-port for redistribution We develop a prime that reduces trust in government without significantly moving respondentsrsquo concern for inequality and poverty respondents exposed to this prime significantly reduce their support for programs that involve the government directly redistributing tax dollars while increasing their support for nongovernmental solutions such as private charity

Only when we explicitly show individuals the concrete effects of government poverty policies do we observe consistent statistically significant increases in sup-port for such policies41 Even so such effects are small and are largest for indirect transfer programs such as the minimum wage that do not involve the government collecting and redistributing tax dollars

Future work might further probe the connection between government trust and policy preferences Underlying mistrust might help to explain the reluctance to sup-port policies that would seem to be in the majorityrsquos self-interest Relatedly distrust could explain why minimum wage increases typically enjoy 70ndash80 percent support in surveys Many economists assume that respondents simply misunderstand the incidence of the minimum wage Instead it might be the case that they view the minimum wage as imperfect but better than other redistributive policies that involve sending money to Washington DC42 In future work it would be valuable to test whether treatments that increase trust in the government also increase support for redistributive policies

As we extensively document the estate tax is the exception to the generally small effects of information on policy even a four-sentence description providing information on its incidence significantly increases support for the policy At least part of this effect appears due to vast misinformationmdashmany respondents both in our survey and past work on the estate tax believe a majority of families are subject to it whereas the actual share is 01 percent

It remains an open question if misinformation fully explains the difference For example Americans might view the moral claims to inheritance versus income differently If the goal of the estate tax is to prevent the self-perpetuation of extreme wealth then respondents might still support it even if say the government merely

41 Future work could also explore how emphasizing the negative aspects of redistribution such as reduced labor supply could affect preferences for redistribution

42 Notably voters in several conservative states passed minimum wage hikes in the 2014 midterm elections consistent with their not viewing the minimum wage as a ldquogovernment programrdquo

burns the money it collects Therefore low levels of trust in government may not inhibit support for the estate tax as much as for other policies where efficiency is a more salient goal Independent of the origin of the treatment effect the large elasticity of support for the estate tax in response to basic information that we and past work have documented is highly policy-relevant given the recent rise in inher-itance flows in many developed countries43

Randomized online surveys are a powerful and convenient tool for studying the effects of information treatments on attitudes and behaviors one we imagine can be used to extend the results we have documented The tool is powerful because it can reach large samples of US residents (in the thousands) at fairly low cost ($1ndash$2 per respondent) It is convenient because using widely available software online surveys are now very easy to design Hence it becomes more feasible to explore mechanisms behind results For example we were able to easily design companion experiments to test mechanisms potentially underlying the effects in our original omnibus treatment Therefore in contrast to field experiments which are very costly to set up and replicate online survey experiments lend themselves naturally to con-ducting series of experiments where results from an initial experiment lead to new experiments to cast light on potential mechanisms

Such flexibility will allow researchers to gain a more nuanced understanding of redistributive preferences While projections are by nature uncertain the US gov-ernment is expected to face a long-run fiscal imbalance largely due to the aging of the population and rising health care costs44 European countries face similar challenges The distributional effects of any future fiscal rebalancingmdashraising taxes cutting spending or bothmdashwill depend in large part on votersrsquo redistributive prefer-ences how strongly they hold them and whether and how they act on them As such these questions are of first-order importance in public economics We believe that the methodology we employed in this paper can be used in future research to better understand how individualsrsquo redistributive preferences are formed and shaped

REFERENCES

Alesina Alberto and George-Marios Angeletos 2005 ldquoFairness and Redistributionrdquo American Eco-nomic Review 95 (4) 960ndash80

Alesina Alberto and Eliana La Ferrara 2005 ldquoPreferences for Redistribution in the Land of Oppor-tunitiesrdquo Journal of Public Economics 89 (5ndash6) 897ndash931

Alesina Alberto F and Paola Giuliano 2011 ldquoPreferences for Redistributionrdquo In Handbook of Social Economics Volume 1A edited by Jess Benhabib Alberto Bisin and Matthew O Jackson 93ndash132 Amsterdam North-Holland

Amir Ofra David G Rand and Yaakov Kobi Gal 2012 ldquoEconomic Games on the Internet The Effect of $1 Stakesrdquo PLoS ONE 7 (2) e31461

Bartels Larry M 2005 ldquoHomer Gets a Tax Cut Inequality and Public Policy in the American Mindrdquo Perspectives on Politics 3 (01) 15ndash31

Bartels Larry M 2009 ldquoEconomic Inequality and Political Representationrdquo In The Unsustainable American State edited by Lawrence Jacobs and Desmond King 167ndash96 New York Oxford Uni-versity Press

43 See Piketty (2014 ch 11) Unfortunately data limitations make it difficult to know whether this trend applies specifically to the United States

44 See eg the Congressional Budget Officersquos 2014 long-run budget projections (wwwcbogovpublication 45471) (accessed December 1 2014)

Beacutenabou Roland and Efe A Ok 2001 ldquoSocial Mobility and the Demand for Redistribution The POUM Hypothesisrdquo Quarterly Journal of Economics 116 (2) 447ndash87

Bernardi Richard A 2006 ldquoAssociations between Hofstedes Cultural Constructs and Social Desir-ability Response Biasrdquo Journal of Business Ethics 65 (1) 43ndash53

Brader Ted 2005 ldquoStriking a Responsive Chord How Political Ads Motivate and Persuade Voters by Appealing to Emotionsrdquo American Journal of Political Science 49 (2) 388ndash405

Corneo Giacomo and Hans Peter Gruumlner 2000 ldquoSocial Limits to Redistributionrdquo American Eco-nomic Review 90 (5) 1491ndash1507

Corneo Giacomo and Hans Peter Gruumlner 2002 ldquoIndividual Preferences for Political Redistributionrdquo Journal of Public Economics 83 (1) 83ndash107

Cruces Guillermo Ricardo Perez-Truglia and Martin Tetaz 2013 ldquoBiased Perceptions of Income Distribution and Preferences for Redistribution Evidence from a Survey Experimentrdquo Journal of Public Economics 98 100ndash12

Dalton Derek and Marc Ortegren 2011 ldquoGender Differences in Ethics Research The Importance of Controlling for the Social Desirability Response Biasrdquo Journal of Business Ethics 103 (1) 73ndash93

Druckman James N and Kjersten R Nelson 2003 ldquoFraming and Deliberation How Citizensrsquo Con-versations Limit Elite Influencerdquo American Journal of Political Science 47 (4) 729ndash45

Edwards Kari 1990 ldquoThe Interplay of Affect and Cognition in Attitude Formation and Changerdquo Journal of Personality and Social Psychology 59 (2) 202ndash16

Fong Christina M 2001 ldquoSocial Preferences Self-Interest and the Demand for Redistributionrdquo Jour-nal of Public Economics 82 (2) 225ndash46

Fujii Edwin T and Clifford B Hawley 1988 ldquoOn the Accuracy of Tax Perceptionsrdquo Review of Eco-nomics and Statistics 70 (2) 344ndash47

Gaines Brian J James H Kuklinski and Paul J Quirk 2007 ldquoThe Logic of the Survey Experiment Reexaminedrdquo Political Analysis 15 (1) 1ndash20

Gelder Marleen M H J van Reini W Bretveld and Nel Roeleveld 2010 ldquoWeb-Based Question-naires The Future in Epidemiologyrdquo American Journal of Epidemiology 172 (11) 1292ndash98

Gerber Alan S James G Gimpel Donald P Green and Daron R Shaw 2011 ldquoHow Large and Long-Lasting are the Persuasive Effects of Televised Campaign Ads Results from a Randomized Field Experimentrdquo American Political Science Review 105 (1) 135ndash50

Gilens Martin 1996 ldquolsquoRace Codingrsquo and White Opposition to Welfarerdquo American Political Science Review 90 (3) 593ndash604

Guillaud Elvire 2013 ldquoPreferences for Redistribution An Empirical Analysis over 33 Countriesrdquo Journal of Economic Inequality 11 (1) 57ndash78

Horton John J David G Rand and Richard J Zeckhauser 2011 ldquoThe Online Laboratory Conduct-ing Experiments in a Real Labor Marketrdquo Experimental Economics 14 (3) 399ndash425

Hoxby Caroline and Sarah Turner 2013 ldquoExpanding College Opportunities for High-Achieving Low Income Studentsrdquo Stanford Institute for Economic Policy Research Discussion Paper 12-014

Huddy Leonie and Anna H Gunnthorsdottir 2000 ldquoThe Persuasive Effects of Emotive Visual Imag-ery Superficial Manipulation or the Product of Passionate Reasonrdquo Political Psychology 21 (4) 745ndash78

Kenworthy Lane and Leslie McCall 2008 ldquoInequality Public Opinion and Redistributionrdquo Socio-Economic Review 6 (1) 35ndash68

Kluegel James R and Eliot R Smith 1986 Beliefs about Inequality Americansrsquo Views of What Is and What Ought to Be New York Aldine de Gruyter

Kreuter Frauke Stanley Presser and Roger Tourangeau 2008 ldquoSocial Desirability Bias in CATI IVR and Web Surveys The Effects of Mode and Question Sensitivityrdquo Public Opinion Quarterly 72 (5) 847ndash65

Kuklinski James H Paul J Quirk Jennifer Jerit David Schwieder and Robert F Rich 2003 ldquoMis-information and the Currency of Democratic Citizenshiprdquo Journal of Politics 62 (3) 790ndash816

Kuziemko Ilyana Michael I Norton Emmanuel Saez and Stefanie Stantcheva 2015 ldquoHow Elastic Are Preferences for Redistribution Evidence from Randomized Survey Experiments Datasetrdquo American Economic Review httpdxdoiorg101257aer20130360

Lecheler Sophie and Claes H de Vreese 2011 ldquoGetting Real The Duration of Framing Effectsrdquo Journal of Communication 61 (5) 959ndash83

Liebman Jeffrey B and Erzo F P Luttmer 2011 ldquoWould People Behave Differently If They Better Understood Social Security Evidence From a Field Experimentrdquo National Bureau of Economic Research Working Paper 17287

Loef Joost Gerrit Antonides and Willem Frederik van Raaij 2001 ldquoThe Effectiveness of Advertis-ing Matching Purchase Motivationrdquo Erasmus Research Institute of Management Research Paper 012001 repubeurnlpub127erimrs20011102140138pdf (accessed February 19 2015)

Luskin Robert C James S Fishkin and Roger Jowell 2002 ldquoConsidered Opinions Deliberative Polling in Britainrdquo British Journal of Political Science 32 (3) 455ndash87

Luttmer Erzo F P 2001 ldquoGroup Loyalty and the Taste for Redistributionrdquo Journal of Political Econ-omy 109 (3) 500ndash528

Luttmer Erzo F P and Monica Singhal 2011 ldquoCulture Context and the Taste for Redistributionrdquo American Economic Journal Economic Policy 3 (1) 157ndash79

Margalit Yotam 2013 ldquoExplaining Social Policy Preferences Evidence from the Great Recessionrdquo American Political Science Review 107 (1) 80ndash103

McCaffery Edward J and Jonathan Baron 2006 ldquoThinking about Taxrdquo Psychology Public Policy and Law 12 (1) 106ndash35

McCall Leslie and Lane Kenworthy 2009 ldquoAmericansrsquo Social Policy Preferences in the Era of Rising Inequalityrdquo Perspectives on Politics 7 (3) 459ndash84

Meltzer Allan H and Scott F Richard 1981 ldquoA Rational Theory of the Size of Governmentrdquo Journal of Political Economy 89 (5) 914ndash27

Norton Michael I and Dan Ariely 2011 ldquoBuilding a Better America One Wealth Quintile at a Timerdquo Perspectives on Psychological Science 6 (1) 9ndash12

Paolacci Gabriele Jesse Chandler and Panagiotis Ipeirotis 2010 ldquoRunning Experiments on Amazon Mechanical Turkrdquo Judgment and Decision Making 5 (5) 411ndash19

Piketty Thomas 1995 ldquoSocial Mobility and Redistributive Politicsrdquo Quarterly Journal of Econom-ics 110 (3) 551ndash84

Piketty Thomas 2014 Capital in the Twenty-First Century Cambridge MA Harvard University Press

Piketty Thomas and Emmanuel Saez 2003 ldquoIncome Inequality in the United States 1913ndash1998rdquo Quarterly Journal of Economics 118 (1) 1ndash41

Piketty Thomas Emmanuel Saez and Stefanie Stantcheva 2014 ldquoOptimal Taxation of Top Labor Incomes A Tale of Three Elasticitiesrdquo American Economic Journal Economic Policy 6 (1) 230ndash71

Rand David G and Martin A Nowak 2011 ldquoThe Evolution of Antisocial Punishment in Optional Public Goods Gamesrdquo Nature Communications 2 434

Rosselli Francine John J Skelly and Diane M Mackie 1995 ldquoProcessing Rational and Emotional Messages The Cognitive and Affective Mediation of Persuasionrdquo Journal of Experimental Social Psychology 31 (2) 163ndash90

Saez Emmanuel and Stefanie Stantcheva 2013 ldquoGeneralized Social Marginal Welfare Weights for Optimal Tax Theoryrdquo National Bureau of Economic Research Working Paper 18835

Saez Emmanuel and Gabriel Zucman 2014 ldquoWealth Inequality in the United States since 1913 Evi-dence from Capitalized Income Tax Datardquo National Bureau of Economic Research Working Paper 20625

Sapienza Paola and Luigi Zingales 2013 ldquoEconomic Experts versus Average Americansrdquo American Economic Review 103 (3) 636ndash42

Savani Krishna and Aneeta Rattan 2012 ldquoA Choice Mind-Set Increases the Acceptance and Main-tenance of Wealth Inequalityrdquo Psychological Science 23 (7) 796ndash804

Senik Claudia 2009 ldquoIncome Distribution and Subjective Happiness A Surveyrdquo Organisation for Economic Cooperation and Development Social Employment and Migration Working Paper 96

Sides John 2011 ldquoStories Science and Public Opinions about the Estate Taxrdquo httphomegwuedu~jsidesestatetaxpdf (accessed February 19 2015)

Singhal Monica 2008 ldquoQuantifying Preferences for Redistributionrdquo httpwwwhksharvardedufsmsinghataxprefs_nov2013pdf (accessed February 19 2015)

Slemrod Joel 2006 ldquoThe Role of Misconceptions in Support for Regressive Tax Reformrdquo National Tax Journal 59 (1) 57ndash75

Suri Siddharth and Duncan J Watts 2010 ldquoCooperation and Contagion in Web-Based Networked Public Goods Experimentsrdquo PLoS ONE 6 (3) e16836

Weinzierl Matthew C 2012 ldquoThe Promise of Positive Optimal Taxation Normative Diversity and a Role for Equal Sacrificerdquo National Bureau of Economic Research Working Paper 18599

Yamamura Eiji 2014 ldquoTrust in Government and Its Effect on Preferences for Income Redistribution and Perceived Tax Burdenrdquo Economics of Governance 15 (1) 71ndash100

Web Appendix of

How Elastic are Preferences for RedistributionEvidence from Randomized Survey Experiments

By Ilyana Kuziemko Michael I Norton Emmanuel Saez andStefanie Stantcheva

A Detailed Description of the Experiment

A1 Omnibus Treatment Description

This Section describes in detail the omnibus experiment The omnibus treatment experimentwas carried out in 4 separate rounds from January 2011 to August 2012 The structure ofthe experiment was as follows(1) Background socio-economic questions including age gender race marital status chil-dren state of residence education household income work status whether the respondentconsiders himself conservative or liberal on economic policy voting choice in 2008 presiden-tial election(2) Randomized treatment showing information on inequality the estate tax and tax policyshown solely to the treatment group Those treatments are illustrated through screenshotsin appendix Figures 1 2 3 and 4(3) Set of questions on inequality taxes and transfers policy views and 2012 voting plansThose questions are listed in detail after the screenshots

Surveys were openly posted on mTurk and their description stated that they would pay$150 for approximately 15 minutes of survey time ie a $6 hourly wage People were freeto drop out any time or take up to one hour to answer all questions

Round 3 was conducted with CT Marketing Group instead of mTurk at a cost of $5 perrespondent The survey software remained exactly the same

The link to this survey is httpshbsqualtricscomSESID=SV_77fSvTy12ZSBihn

List of all Outcome Questions

Note Sentences in italic were not seen by the respondents Bold fonts are just labels for eachsection Sentences in normal font are exactly as they appeared in the survey Text in bracketrepresents the answer choices given to respondents Text in curly brackets are explanatorynotes for the readers of this paper (not presented to respondents)

Tax rate questions

1 Choose the tax rate on the top 1 next 9 next 40 and bottom 50 (see screenshot)[Slider with continuous percentage choices 0-100 for each of the four income groups]

2 Do you think top income tax rates were higher in the 1950s and 1960s than they aretoday [Yes higher in the 1950s and 1960sNo lower in the 1950s and 1960s]

1

3 As you may know there have been proposals recently to decrease the federal deficitby raising income taxes on millionaires Do you think income taxes on millionaires shouldbe increased stay the same or decreased [IncreasedStay the sameDecreased]

4 The Federal Estate tax (also known as the Death Tax) is a tax imposed on the transferof wealth from a deceased person to his or her heirs Do you think the Federal Estate taxshould be decreased left as is or increased [DecreasedLeft as isIncreased]

First stage questions on knowledge and perceptions of inequality

5 Do you think annual economic growth was faster in the period 1980-2010 than in theperiod 1933-1980 [Faster in 1980-2011The same in both periodsFaster in 1933-1980]

6 Do you think inequality is a serious problem in America [Not a problem at allAsmall problemA problemA serious problemA very serious problem]

7 Do you think income inequality in the US has increased or decreased in recent decades[DecreasedStayed the sameIncreased]

8 Are you satisfied with your current income [Very satisfiedSomewhat satisfiedNottoo satisfiedNot at all satisfied]

9 Do you think that the very high earners in our society deserve their high incomes[Most of the timeSometimesRarely]

10 Which statement do you agree with most [A ldquoOnersquos income and position in societyis mostly the result of onersquos individual effortrdquo BldquoOnersquos income and position in society is toa large extent the outcome of elements outside of onersquos control (for example including butnot limited to family background luck health issues etc)rdquo]

Political Outcomes

11 Which party do you plan to support in the 2012 presidential elections [Demo-craticRepublicanOtherNone] note the surveys were carried out before the 2012 elec-tions

12 How much of the time do you think you can trust government in Washington to dowhat is right [Just about alwaysMost of the time Only some of the time Never]

13 Next think more broadly about the purpose of government Where would you rateyourself on a scale of 1 to 5 where 1 means you think the government should do only thosethings necessary to provide the most basic government functions and 5 means you think thegovernment should take active steps in every area it can to try and improve the lives of itscitizens [12345]

14 What do you think the most important goal of the federal income tax should be [Raisemoney for infrastructure projects such as roads and bridges Raise money for universal socialservices such as Social Security and Medicare Raise money from the wealthiest citizens tosupport programs that aid low-income citizens such as Medicaid and Food Stamps)]

Poverty Reduction Policies Outcomes

15 The minimum wage is currently $725 per hour Do you think it should be decreasedstay the same or increased [DecreasedStay the sameIncreased]

16 Do you support or oppose the Earned Income Tax Credit (EITC) program [Sup-portIndifferentOppose]

17 Do you support or oppose the Food Stamps program [SupportIndifferentOppose]

2

18 In the next month do you plan to donate any money to an organization that supportsthose in need [YesNo]

19 In the past month have you donated any money to an organization that supportsthose in need [YesNo]

20 In the next month do you plan to donate some of your time to an organization thatsupports those in need [YesNo]

21 In the past month have you donated some of your time to an organization thatsupports those in need [YesNo]

Real Outcome Petition for Estate Tax

22 Writing to the Senators of your state gives you an opportunity to influence taxationpolicy Few citizens email their elected officials therefore Senators and their staff take suchemails from their constituents very seriously If you would like to write to your Senator go tothe official US Senate list and click on your Senatorrsquos contact webpage Two sample lettersare provided below one asking for higher estate taxes on the rich one asking not to increaseestate taxes on the rich Feel free to cut-and-paste and edit the text before sending it to yourSenator Most Senatorsrsquo websites ask for your name and address to avoid spam We are notable to record what you write on the external (Senatorrsquos) website so your letter and privateinformation are kept fully confidential

For the purpose of our survey we would just like to know from you I sent or will send anemail to my Senator asking for higher estate taxes on the rich I sent or will send an emailto my Senator asking to not increase estate taxes on the rich I do not want to email mySenator

Sample letter for higher estate taxes on the rich Dear Senator In the coming monthsas you debate the federal budget one of the priorities for Congress should be raising estatetaxes on the wealthiest Americans so that they pay their fair share to fund governmentprograms and help solve our federal budget deficit problem

Sample letter for not increasing estate taxes on the rich Dear Senator In the comingmonths as you debate the federal budget one of the priorities for Congress should be keepingestate taxes on the wealthiest Americans low The government should not punish people whoare financially successful or well-off

[I sent or will send an email to my Senator asking for higher estate taxes on the richIsent or will send an email to my Senator asking to not increase estate taxes on the richI donot want to email my Senator]

A2 Estate Tax Experiment Description

The follow up estate tax experiment was conducted in March 2014 on a sample of 1800respondents Respondents were randomized into one of two treatment groups or into thecontrol group The first treatment group saw the same screen as in the omnibus treatment(only the part regarding the estate tax) as in appendix Figure 4 The second group saw aplain explanation for the estate tax as in appendix Figure 6

The link to this experiment is httpshbsqualtricscomSESID=SV_0vOecp2MDPBpInb

3

Note Sentences in italic were not seen by the respondents Bold fonts are just labels for eachsection Sentences in normal font are exactly as they appeared in the survey

2 Do you think income inequality in the United States has increased or decreased since1980 [DecreasedStayed the sameIncreased]

4 The Federal Estate Tax is a tax imposed on the transfer of wealth from a deceased per-son to his or her heirs What percentage of people who die have to pay the Federal Estate taxIf you donrsquot know just give your best guess [Less than 1110204060100]

5 Do you think poverty is a serious problem in America [Not a problem at allA smallproblemA problemA serious problemA very serious problem]

7 Do you think the federal estate tax should be decreased left as is or increased (Recallthat the federal estate tax is a tax imposed on the transfer of wealth from a deceased personto his or her heirs) [DecreasedLeft as isIncreased]

8 As you may know there have been proposals recently to decrease the federal deficitby raising income taxes on millionaires Do you think income taxes on millionaires shouldbe increased stay the same or decreased[IncreasedStay the sameDecreased]

9 Which of the tools below do you consider the best to address inequality in the UnitedStates Please drag and drop the items to the box on the right and rank them in yourpreferred order Your preferred method for addressing inequality should be at the top yourleast preferred one at the bottom [Education Policies Private Charity Progressive TaxesGovernment Transfers (eg food stamps Medicaid) Government regulation (eg minwage caps on top compensation)]

10 Should the federal government increase or decrease spending on aid to the poor[Significantly increaseSlightly increaseKeep at current levelSlightly decreaseSignificantlydecrease]

11 The federal minimum wage is currently $725 per hour Do you think it should bedecreased stay the same or increased [Significantly increasedSlightly increasedStay thesameSlightly decreasedSignificantly decreased]

12 Should the federal government increase or decrease its spending on public housing forlow income families [Significantly increase Slightly increaseKeep at current levelSlightlydecreaseSignificantly decrease]

13 Should the federal government increase or decrease its spending on food stamps(Food stamps provide financial assistance for food purchasing to families and individuals withlow or no income) [Significantly increaseSlightly increaseKeep at current levelSlightlydecreaseSignificantly decrease]

14 Petition for Estate Tax same as in A115 Which party do you plan to support in the 2014 congressional elections [Demo-

craticRepublicanOtherNone]16 How much of the time do you think you can trust government in Washington to do

what is right [Just about alwaysMost of the timeOnly some of the timeHardly ever]

4

18 Do you think that people in the government waste a lot of money we pay in taxeswaste some of it or donrsquot waste very much of itrdquo [Waste a lot of money we pay intaxesWaste some of the money we pay in taxesDonrsquot waste much of the money we pay intaxes]

19 How do you feel about the following statement ldquoCurrently the federal government isvery effective in limiting fraud waste and abuse in the programs it administersrdquo [StronglyagreeAgreeDisagreeStrongly disagree]

20 How do you feel about the following statement ldquoPoliticians in Washington work toenrich themselves and their largest campaign contributors instead of working for the benefitof the majority of citizensrdquo [Strongly agreeAgreeDisagreeStrongly disagree]

A3 Emotional Poverty Experiment

The emotional poverty treatment was conducted in March 2014 on a sample of 1200 respon-dents Respondents were first as usual asked for their demographic information Dependingon their answers to the questions about their marital status and whether they have childrenliving with them they were redirected to a specific customized branch They were thenrandomized into treatment and control group The treatment group saw information aboutpoverty that was adapted to their family situation without knowing that the informationwas actually customized Each respondent estimated the basic expenses that a family of theconfiguration of his own family (living where the respondent lives) would have to incur forrent utilities transportation to work food and depending on the family situation expensesfor children Appendix Figure 9 shows the screenshot where respondents were asked to es-timate the minimal budget of a family similar to theirs Between this page and the nextthe program computed the total expenses estimated If those were above the actual povertythreshold for the family the next page told respondents that given their estimates the familywould fall short by such and such amount If the total was below the poverty threshold thenext page told respondents that given their estimates the family would only be left withsuch and such amount for all other expenses

The link to the survey is httpshbsqualtricscomSESID=SV_1B8MczKSMIvWaqx

The outcome questions were the same as in section A2 except that the question abouthow many people pay the estate tax was not asked Instead the following three questionswere added

1 What percentage of Americans live in poverty If you donrsquot know just give yourbest guess (Poverty is officially defined as having monthly resources below $970 for a singleperson $1310 for a two person family $1650 for a three person family etc) [Less than 5 9 16 24]

2 What percentage of children under age 18 live in poverty in the US approximatelyIf you donrsquot know just give your best guess [10 20 30 40]

5

3 How many workers in the US earn the minimum wage If you donrsquot know just giveyour best guess [2 million 6 million 10 million]

A4 Policy Experiment

The policy experiment was conducted in March 2014 on a sample of 1300 respondents Re-spondents were randomized into a control group or a treatment group The treatment groupwas again redirected to a customized branch depending on their answers to the questionsabout their marital status and whether they had children living with them In the treatmentscreens they were asked about and shown information about a family whose configurationwas similar to theirs First respondents were asked to estimate the minimum expenses neces-sary for a family earning the minimum wage for rent utilities transportation to work foodand if applicable children expenses That screen is shown in appendix Figure 10 Betweenthis page and the next the program computed the total expenses implied and informed therespondents either of the shortfall that the family living on a single minimum wage wouldhave to face or the surplus that would be left over if they had to incur the expenses asestimated by the respondent That second screen also showed information about the foodstamps program informing respondents that ldquoThe Food Stamps program helps many lowincome families such as those earning only one minimum wage It provides $150month perperson to help with food expensesrdquo

The link to the experiment is httpshbsqualtricscomSESID=SV_1B8MczKSMIvWaqxThe outcome questions were exactly the same as in section A3

A5 Trust Experiment

The trust treatment was conducted in March 2014 on a sample of 1000 respondents Thetreatment showed people information about how the United States is ranked in terms ofcorruption among a list of countries of similar income and development levels (the UnitedStates is ranked in the worst group of countries given income and development levels) asshown in appendix Figure 8

The link to this survey is in httpshbsqualtricscomSESID=SV_bgEuJfl1Y3UreKhRespondents in the treatment group were asked questions designed to elicit negative

reactions regarding the government The full list of questions were1 What is your view of the ldquoWall Street bailoutrdquo the legislation signed into law by

President Bush in 2008 whereby the federal government lent $700 billion to banks and otherfinancial institutions that faced bankruptcy [Strongly support this legislationSupport thislegislationOppose this legislationStrongly oppose this legislation]

2 Because of a recent Supreme Court decision for the first time in decades there are nowno limits on the amount of money that corporations and other special interests can give topolitical campaigns for President or Congress Do you agree with the following statementldquoCorporations and other specials interests have far too much influence on politicians inWashingtonrdquo [Strongly agreeAgreeDisagreeStrongly disagree]

6

4 How much confidence do you have in the federal governmentrsquos administering of eco-nomic and military aid to foreign countries (which totals over $50 billion annually) [A greatdeal of confidenceSome confidenceLittle confidenceNo confidence]

The outcome questions were the same as in section A2 except that we did not ask anyof the knowledge questions about poverty rates child poverty rates minimum wage earnersor how many people pay the estate tax

A6 List of all constructed variables

Below we provide a full definition of all variables used in the tables In brackets we providethe coding of the variable

bull ldquoIneq vsrdquo (or ldquoIneq v seriousrdquo) is a binary variable equal to 1 if the respondent repliesthat ldquoinequality is a very serious problemrdquo [01]

bull ldquoIneq incrdquo (or ldquoIneq increasedrdquo) is a binary variable equal to 1 if the respondentreplies that inequality has increased since 1980 [01]

bull ldquoDeservingrdquo (or ldquoRich deservingrdquo) is a binary variable equal to 1 if the respondentbelieves that the rich are deserving of their income ldquomost of the timerdquo [01]

bull ldquoTop taxrdquo (or ldquoTop tax raterdquo) is the chosen average tax rate on the richest one percent[0 to 100]

bull ldquoMill taxrdquo (or ldquoIncrease Mill Taxrdquo) is an indicator variable for whether the respondentwants to increase the income tax on millionaires [01]

bull ldquoEstate taxrdquo (or ldquoIncrease Estate Taxrdquo) is an indicator variable for whether the re-spondent wants to increase the estate tax [01]

bull ldquoPetitionrdquo is an indicator variable for whether the respondent wants to send a petitionto her State Senator to increase the estate tax [01]

bull ldquoMin wagerdquo in the omnibus treatment indicates support for increasing the minimumwage [01]

bull ldquoMin wagerdquo in the follow up surveys indicates the strength of the support for increasingthe minimum wage [01234 increasing in support]

bull ldquoAidrdquo indicates support for expanding aid to the poor [01234 increasing in sup-port]

bull ldquoHousingrdquo indicates support for expanding funding for public housing [01234increasing in support]

7

bull ldquoFood stampsrdquo in the omnibus indicates support for expanding the food stamps pro-gram [01]

bull ldquoFood stampsrdquo in the followup surveys indicates the strength of the support for ex-panding the food stamps program [01234 increasing in support]

bull ldquoEITCrdquo indicators support for expanding funding for the EITC [01]

bull ldquoTrustrdquo or (ldquoTrust govtrdquo) is an indicator variable for whether the respondent believesthe government can be trusted [01]

bull ldquoScoperdquo (or ldquoGovt scoperdquo) is a categorical variable indicating how active the govern-ment should be in redistributing income [12345 5 being the broadest scope ofgovernment]

bull ldquoDem 2012rdquo indicates that the respondent plans to vote for the Democrat (Obama) inthe 2012 Presidential election [01]

bull ldquoDem 2014rdquo indicates that the respondent plans to vote for the Democrat in the 2014Congressional election [01]

bull ldquoTaxes redistrrdquo indicates that the respondent thinks that the role of income taxes isto redistribute income (as opposed to just financing infrastructure) [01]

bull ldquoGrowthrdquo indicates that the respondentrsquos reply to the question of whether growth washigher in 1933-1980 than in 1980-200 was correct [01]

bull ldquoTax 1950rdquo indicates that the resppndentrsquos reply to the question whether top incometaxes were higher in the 1950s than today was correct [01]

bull ldquoSatisfiedrdquo indicates whether the respondent is satisfied with his current income [01]

bull ldquoMoney charityrdquo is a dummy variable for whether the respondent plans to give moneyto charity in the next month [01]

bull ldquoMoney givenrdquo indicates whether he has already given money in the past month [01]

bull ldquoTime charityrdquo is a dummy variable for whether the respondent plans to give time tocharity in the next month [01]

bull ldquoTime givenrdquo indicates whether he has already given time in the past month [01]

bull ldquoIncome mostly result of effortrdquo is a binary variable indicating that the respondentbelieves that onersquos income is mostly the result of onersquos own effort [01]

bull ldquoTax on next 9rdquo rdquoTax on next 40 rdquo and rdquoTax on Bottom 50rdquo are the respondentrsquoschosen tax rates for respectively people in the 90th to 99th percentile in the 50th to90th percentile and in the Bottom half of the income distribution [0 to 100]

bull ldquoDiff tax top 1 and Bottom 50rdquo is the tax differential between the preferred tax on thetop 1 and that on the Bottom 50

8

bull ldquoCharitiesrdquo refers to the ranking (from 1 to 5 with 1 being the highest ranking) that re-spondents attribute to private charities as a means to redistribute income [12345]

bull ldquoEduc polrdquo refers to the ranking (from 1 to 5 with 1 being the highest ranking)that respondents attribute to education policies as a means to redistribute income[12345]

bull ldquoNo wasterdquo takes values from 1 to 3 with 1 representing that the government is wastinga lot of tax revenue and 3 indicating that the government is not wasting much taxrevenue at all [123]

B Methodological issues related to online survey experiments

In this section we share what we have learned through our experience with these mTurk sur-vey experiments to highlight both the advantages and disadvantages of using online surveysfor research as well as provide advice for future researchers

The most obvious advantage is the ease and speed of gathering relatively large samplesAt a per-survey price of $150 it typically took at most five or six days to gather a sample of1000 US residents and samples of 300-400 could usually be gathered within 24 hours Animportant piece of advice for future researchers studying American domestic policy questionsis to ask mTurk to limit the sample to US residents (Amazon documents this informationfor tax purposes) In pilot surveys we conducted before becoming aware of this problem overforty percent of our respondents turned out to have non-US IP addresses (likely an evergreater share were foreign residents since respondents can connect through remote serversand appear to be in the US) Launching surveys at night (during the workday in Asia)exacerbates this problem

B1 How representative is the mTurk sample

As noted earlier respondents to our surveys are not representative of the US populationHowever this lack of representativeness does not appear substantially worse than in othersurveys For example the mTurk sample is about 13 years younger and 13 percentage pointsmore likely to have a college degree than the representative sample of US adults in ournational CBS sample (see Table 1) But that same CBS poll we use as a basis for comparisonis itself weighted The raw CBS sample is about nine years older than the weighted sampleand like our mTurk sample about 13 percentage points more likely to have a college degreeIt under-represents Hispanics to the same extent as our sample and is even worse than oursample in terms of the under-representation of men As such while the mTurk sample is notrepresentative neither are other standard polls (though some of the biases such as age arein opposite directions from standard polls)

As noted in the text the American Life Panel is more representative than the mTurksample However this sample is much smaller and roughly 30 times more expensive thanmTurk

9

B2 How serious is attrition in the mTurk sample

As noted earlier for the omnibus treatment we have an overall attrition rate (the share ofrespondents who start but do not finish the survey) of 22 percent a 21 percent rate for theCT Marketing Group survey and a 22 percent rate for the mTurk surveys In fact whenwe compare surveys 4 and 5mdashwhich were in the field at the same time with the former onmTurk and the latter on CT Marketing Groupmdashattrition is actually lower on mTurk EvenGallup has an attrition rate of nine percent on its 15-minute Daily Poll1 Given that oursurvey requires people to read through informational treatments we suspect that a pureopinion survey conducted on mTurk would have a lower attrition rate

The omnibus survey has differential attrition between treatment and control probablybecause of the relatively long length of the treatment (respondents had to scroll through6 treatment pages in the omnibus survey) Importantly the follow-up surveys do not havesuch differential attrition because the treatment was much shorter (2 pages at most) so thatthere was no noticeable length difference between the treatment and control group

A related point is that researchers using this methodology should ask background ques-tions first In settings with little to no attrition background questions can ideally be askedat the very end to avoid priming but given the importance of assessing non-random attri-tion it may be preferable for online survey experiments to ask demographic and backgroundquestions at the outset

B3 How many unique observations can one collect on mTurk

Although the exact number of workers registered on mTurk is not publicly reported thepool is thought to be quite large approximately 500000

However the pool available for any given survey experiment is more limited First work-ers select into tasks voluntarily choosing among types of tasks As a result the pool ofworkers interested in survey experiments is more limited Indeed survey experiments aretypically longer than a standard task on mTurk and might require more attention Secondwe filter workers based on past ratings this is to avoid careless workers who consistentlydo not complete tasks properly and have been rated negatively by previous amazon mTurkrequesters (ie employers on mTurk) Third the pool of registered workers is not online allthe time Many workers could be working for a few weeks then switch to another occupa-tion and potentially come back later or only work during some times of the year monthor week Finally there is competition between tasks Many tasks are posted simultaneouslyon the platform and workers have to search for each individual task Large sample surveyexperiments sometimes fall lower in the list and are less visible to workers (although oneway to make it more visible and which we employ is to stop and relaunch the survey severaltimes so that it moves back up to the top of the list of tasks)

We always exclude workers who have already taken one of our survey experiments in thepast to avoid any spillovers from previous treatments Hence we need a fresh sample everytime Accordingly we noticed that when we launch a survey experiment several weeks after a

1Email correspondence when Jeffrey Jones at Gallup January 16 2013 The nine-percent figurerefers to all Daily Polls from 2012

10

previous one we easily get a large sample very quickly However when we repeatedly launchexperiments one after the other the rate at which we get workers slows down

To mitigate the constraint of being unable to reach a sufficiently large sample of workersresearchers can do all of the following a) leave sufficient times between survey dates b)pay sufficiently high wages to make the tasks competitive relative to others c) keep surveytime short d) choose more generic titles for the task such as ldquoOpinion Surveyrdquo rather thanldquoAcademic Research Survey in Economicsrdquo However researchers should be warned thateven after taking these steps survey samples are not unlimited in mTurk and if ldquofreshrdquorespondents are needed for each survey date a large share of respondents clicking on the taskwill be screened out (or will need to be dropped ex-post based on repeated mTurk workerIDs)

11

Appendix Figure 1 Inequality Component ldquoWhere are you in the income distributionrdquo

Notes This interactive slider allows people to explore the income distribution in the US and todetermine their position in it Available online athttpshbsqualtricscomSESID=SV_77fSvTy12ZSBihn

12

Appendix Figure 2 Inequality component ldquoWhere would you have been in the incomedistributionrdquo

Notes This interactive slider shows the ldquocounterfactualrdquo household income had income growthbeen shared equally since 1980 Available online athttpshbsqualtricscomSESID=SV_77fSvTy12ZSBihn

13

Appendix Figure 3 Taxes component Correlation between growth and top tax rates overtime

14

Appendix Figure 4 Showing information about the estate tax

Notes Available online athttpshbsqualtricscomSESID=SV_77fSvTy12ZSBihn

15

Appendix Figure 5 Preferred tax rates outcome

16

Appendix Figure 6 Neutral information about the estate tax

Source Calculations based on IRS Estate Tax Statistics

Neutral Treatment

These page timer metrics will not be displayed to the recipient

First Click 0 seconds

Last Click 0 seconds

Page Submit 0 seconds

Click Count 0 clicks

The Federal Estate Tax applies when a deceased person leaves more than $5 million in wealth to his or her heirsWealth left to a spouse or charitable organizations is exempt from estate tax

Only 1 person out of 1000 is wealthy enough to face the estate tax

Average Americans have far less than $5 million in wealth when they die so the estate tax does not affect them and theycan pass on their property to their children tax-free

Control Group

Qualtrics Survey Software httpssqualtricscomControlPanelAjaxphpaction=GetSurve

4 of 11 41314 444 PM

Notes Available online athttpshbsqualtricscomSESID=SV_0vOecp2MDPBpInb

17

Appendix Figure 7 A word cloud based on open-ended responses to the question ldquoHow muchof the time can you trust the government in Washington to do what is rightrdquo

Notes Based on the pilot group survey on mTurk described in Section 42

18

Appendix Figure 8 Negative information about corruption in the US

Q75How do you feel about the following statement Politicians in Washington work to enrichthemselves and their largest campaign contributors instead of working for the benefit of themajority of citizens

Strongly agree Agree Disagree Strongly disagree

Page Break

Q67Each year the non-partisan organization Transparency International rates countries based on theamount of government corruption When the US is compared to countries with similar levels ofincome and development how do you think it ranks

The best 6 Better than average Worse than average The worst 6

Page Break

Q68These are the actual results from the report

Qualtrics Survey Software httpssqualtricscomControlPanelClientAction=EditSurve

2 of 3 61514 643 AM

Notes Available online athttpshbsqualtricscomSESID=SV_bgEuJfl1Y3UreKh

19

Appendix Figure 9 Customized information about poverty

Think about a family of four with two parents working full time at low pay and two kids What would be the minimal monthly expenses that such a family would have to make to afford living inyour city Please enter numbers only with no $ sign and no commas eg 1000

Rent

Utilities (electric heatingcablephone)

Car payment + car insurance + gasto go to work

Food

Child care while working

Married 2 kids Poverty Block 2

50 million of Americans or 16 of the population are living in poverty For a family of four with two children the povertythreshold is $1990month

Based on the numbers you gave the family at the poverty threshold would be left with only $InvalidExpression-$qQID535ChoiceTextEntryValue2-$qQID535ChoiceTextEntryValue3-$qQID535ChoiceTextEntryValue4-$qQID535ChoiceTextEntryValue5month for all other expenses

18 of 37 4214 1104 AM

Notes Available online athttpshbsqualtricscomSESID=SV_1B8MczKSMIvWaqx

20

Appendix Figure 10 Customized information about policies

health care

Single no kids control

Please click on Next

Married kids block 1

Think about a family of four with one parent working full time at the minimum wage and two kids What would be the minimal monthly expenses that such a family would have to make to afford livingwhere you live Please enter numbers only with no $ sign and no commas eg 1000

Rent

Transportation (public transit fareandor car payments insurancegashellip)

Food

Expenses related to children

The current federal minimum wage is $725hour Thatrsquos a net of $1100month when working 40 hoursweek

About 6 million US workers are paid the minimum wage Based on the numbers you gave the family of four with one minimum wage worker and 2 children would be left with only

$Invalid Expression-$qQID455ChoiceTextEntryValue2-$qQID455ChoiceTextEntryValue

16 of 37 4214 1104 AM

21

Appendix Table 1 Share of treatment respondents correctly answering basic comprehensionquestions

(1)Percent that answered correctly

Pct of households earn less than 386000 0866Pct of households earn less than 108000 0855Pct of households earn less than 33800 0838Household now making 386000 would be making 0484Household now making 108000 would be making 0414Household now making 33800 would be making 0395

Observations 2417

Notes This table displays the percent of respondents who answered the comprehension questionscorrectly during the treatment (see the treatment screenshots in the Appendix for the completewording and outlay of these questions)

Appendix Table 2 Ability of covariates to predict whether respondents finish the survey

Variable Coeff P-val

Voted for Obama in 2008 0014 0227Age -0003 0000Liberal policy view 0002 0676Household income 0001 0449Married 0008 0480Education -0001 0724Male 0018 0105Black -0006 0765Hispanic 0072 0007Native -0011 0624Employed full time -0008 0483Unemployed 0024 0145Not in labor force -0029 0055Student 0023 0137Treatment Group -0113 0000

Notes For each row the coefficient and p-value are from regressions of the form Finishedir =α+βCovariatei + δr + εir where Covariate is listed to the left in the row and δr are survey roundfixed effects

22

Appendix Table 3 Attrition by survey round

Survey Attrition Obs (Completed)Control Treatment Differential

Omnibus 009 021 011 4045Estate Tax 006 003 -003 1760Trust 003 002 -001 901Poverty 003 002 -001 1003Policy 006 004 -002 1114

Notes Note that the attrition numbers count those respondents who started and continued longenough to be at least assigned a treatment status Respondents could drop out before being assignedto treatment for a variety of reasons including that they were not US citizens (albeit US residents)or did not agree with the consent form

23

Appendix Table 4 Effect of omnibus treatment on all outcomes part 1

Ineq vs Ineq inc Deserving Top tax Mill tax Estate tax Petition Min wage Food stamps EITC Trust Scope

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Treated 0104lowastlowastlowast 0120lowastlowastlowast -00526lowastlowastlowast 0931lowast 00502lowastlowastlowast 0357lowastlowastlowast 00648lowastlowastlowast 00325lowastlowast 00149 00212 -00292lowastlowast 0132lowastlowastlowast

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

Control mean 0285 0738 0180 3021 0740 0171 0234 0690 0686 0611 0158 3076Scaled Effect 0365 0540 0182 00914 0111 2043 0394 00995 00369 00698 1250 0110Obs 3703 3704 3690 3741 3704 3673 3060 3690 3690 3690 3702 3704

Notes The first three outcome variables are binary indicator variables coded as one if the respondent says that ldquoinequality is a very seriousproblemrdquo ldquoinequality has increasedrdquo and ldquothe rich are deserving of their incomerdquo respectively ldquoTop raterdquo is continuous (respondentsrsquopreferred average tax rate on the richest one percent) ldquoMill taxrdquo and ldquoEstaterdquo indicate the respondent wants income taxes on millionairesand the estate tax to increase respectively ldquoPetitionrdquo indicates she would write her Senator to increase the estate tax ldquoMin wagerdquo ldquoFoodstrdquo and ldquoEITCrdquo indicate support for increasing the minimum wage and funding for SNAP and EITC respectively ldquoTrustrdquo indicatestrust in government and ldquoScoperdquo indicates the respondent favors a broad range of interventions by the government (1-5 categoricalvariable) ldquoCovariatesrdquo and ldquoscaled effectsrdquo are as specified in the notes to Table 4 The row ldquoControl meanrdquo reports the mean of theoutcome variable in the control group lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

24

Dem 2012 Taxes redistr Growth Tax 1950 Satisfied Money charity Money given Time charity Time given

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Treated 00152 00396lowastlowastlowast 0137lowastlowastlowast 0131lowastlowastlowast -00266 000717 000565 000188 -000655[00125] [00132] [00160] [00158] [00264] [00157] [00158] [00160] [00157]

Control mean 0529 0199 0437 0556 2881 0559 0523 0480 0378Scaled Effect 00246 0314 0946 0927 0102 0167 00823 00219 0255Obs 3703 3700 3696 3619 3690 3681 3683 3684 3684

Notes ldquoDem 2012rdquo indicates the respondent plans to vote for the Democrat (Obama) in the 2012 Presidential election ldquoTaxes redistrrdquoindicates that the respondent thinks the role of income taxes is to redistribute income ldquoGrowthrdquo indicates that the respondent correctlyreplied to the question of whether growth was higher in 1933-1980 than in 1980-2000 ldquoTax 1950rdquo indicates that the respondent correctlyreplied to the question whether top income taxes were higher in the 1950s than today ldquoSatisfiedrdquo indicates whether the respondent issatisfied with his current income ldquoMoney charityrdquo (respectively ldquoTime charityrdquo) is a dummy variable for whether the respondent plansto give money (respectively time) to charity in the next month and ldquoMoney givenrdquo (respectively ldquoTime givenrdquo) indicates whether hehas already given money (respectively time) in the past month ldquoCovariatesrdquo and ldquoscaled effectsrdquo are as specified in the notes to Table4 The row ldquoControl meanrdquo reports the mean of the outcome variable in the control group lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

25

Income due to effort Tax on top 1 Tax on next 9 Tax on next 40 Tax on Bottom 50 Top 1 tax - Bottom 50 tax

(1) (2) (3) (4) (5) (6)

Treated -00571lowastlowastlowast 0931lowast -0311 -0593lowast 0304 0628[00152] [0549] [0380] [0341] [0442] [0428]

Control mean 0419 3021 1760 1071 1893 1128Scaled Effect 0156 00914 0195 0232 00531 0140Obs 3689 3741 3740 3721 3741 3741

Notes ldquoIncome due to effortrdquo is a binary variable indicating that the respondent believes that onersquos income is mostly the result of onersquosown effort ldquoTax on top lsquordquo ldquoTax on next 9rdquo rdquoTax on next 40 rdquo and rdquoTax on Bottom 50rdquo are the respondentrsquos chosen tax rates forrespectively people in the 99th percentile 90th to 99th percentile in the 50th to 90th percentile and in the Bottom half of the incomedistribution ldquoTop 1 tax - Bottom 50 taxrdquo is the tax differential between the preferred tax on the top 1 and that on the Bottom 50ldquoCovariatesrdquo and ldquoscaled effectsrdquo are as specified in the notes to Table 4 The row ldquoControl meanrdquo reports the mean of the outcomevariable in the control group lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

26

Appendix Table 7 Selection into the follow-up

Variable Coefficient P-value

Voted for Obama in 2008 -0001 0957Age 0002 0029Liberal policy view -0011 0285Household income 0006 0101Married 0056 0014Education 0007 0389Male -0009 0677Black 0041 0348Hispanic 0079 0177Native -0059 0216Employed full time 0003 0897Unemployed 0004 0901Not in labor force 0080 0038Student -0064 0020

Notes For each row the coefficient and p-value are from regressions of the formFollowupir = α+ βCovariatei + εir where Covariate is listed to the left in the row Those testsare used to detect selection into the follow-up survey

27

Appendix Table 8 Effect of omnibus treatment one month later

Ineq v serious Ineq inc Rich deserving Top tax rate

(1) (2) (3) (4) (5) (6) (7) (8)First Follow-up First Follow-up First Follow-up First Follow-up

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

Notes All outcomes are as defined previously For each dependent variable Col ldquoFirstrdquo is the result from the first survey while ColldquoFollow-uprdquo is the result from the follow-up survey All regressions include our standard controls lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

Appendix Table 9 Effect of omnibus treatment one month later (cont)

Mill tax Estate tax Trust gov Govt scope

Treated -000817 00273 0337lowastlowastlowast 0195lowastlowast -0122lowastlowast -00691 0259 0364lowast

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

Appendix Table 10 Bounding effects of attrition (using ldquoliberalrdquo and ldquoconservativerdquo valuesfor outcomes)

Ineq v serious Increase Mill Tax Increase Estate Tax Trust Gov

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

Treated 00666lowastlowastlowast 00980lowastlowastlowast 000915 00503lowastlowastlowast 0284lowastlowastlowast 0310lowastlowastlowast -00232lowastlowast -00221lowastlowast

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

Notes All outcomes are as defined previously No controls are included For each dependent variableCol C assumes that all attritors gave the average answer among those who label themselves asconservative or very conservative Col L assumes that all attritors would have given the averageanswer among those who label themselves as liberal or very liberal lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

29

Appendix Table 11 Views on inequality and taxes for high- and low-attrition rounds in the omnibus surveys

Ineq v serious Ineq increased Rich deserving Top tax rate Increase Mill Tax Estate tax

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Treated 00794lowastlowastlowast 0117lowastlowastlowast 00849lowastlowastlowast 0138lowastlowastlowast -000327 -00672lowastlowastlowast 0155 2003lowastlowastlowast 00183 00555lowastlowastlowast 0421lowastlowastlowast 0365lowastlowastlowast

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

Control mean 0276 0289 0767 0780 0160 0180 3440 2888 0794 0754 0179 0178Scaled Effect 0278 0387 0475 0615 00118 0209 00131 0203 00487 0108 1761 2396Differential attrition Low High Low High Low High Low High Low High Low HighObs 1260 1635 1260 1636 1254 1631 1271 1650 1260 1636 1250 1626

Notes All outcomes are as defined previously ldquoDifferential attritionrdquo separates observations according to whether they were in ldquoLowrdquodifferential attrition round (round 4) or in ldquoHighrdquo differential attrition rounds (rounds 1 2 and 3) Otherwise all terminology followsthat in previous tables lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

Appendix Table 12 Opinions on other policies and views of government for high- and low-attrition rounds in the omnibussurveys

Min wage EITC Food stamps Trust gov Scope

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Treated 000695 00408lowast -00199 00260 00203 00197 -00630lowastlowastlowast 0000987 00576 0248lowastlowastlowast

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

Control mean 0708 0706 0683 0589 0710 0702 0181 0133 3140 2997Scaled Effect 00227 0129 00679 00808 00490 00451 5724 00311 00441 0195Differential attrition Low High Low High Low High Low High Low HighObs 1254 1631 1254 1631 1254 1631 1259 1635 1260 1636

Notes See previous table lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

30

Appendix Table 13 Effect of estate-tax-only treatments on outcome variables

Ineq vs Ineq inc Estate corr Pov vs Deserving Top tax Mill tax Estate Petition Charities Educ pol

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

Treated (Emotional) 00381 -000239 0316lowastlowastlowast 00224 -00247 1595 000123 0289lowastlowastlowast 00313 00421 -00319[00258] [00243] [00263] [00274] [00206] [1121] [00243] [00258] [00208] [00699] [00755]

Treated (Neutral) 00511lowastlowast -00501lowastlowast 0375lowastlowastlowast 00191 -00244 2280lowastlowast -000456 0109lowastlowastlowast 00239 -00214 00157[00259] [00244] [00264] [00276] [00206] [1124] [00244] [00259] [00209] [00701] [00757]

Control mean 0307 0771 0120 0285 0174 3367 0717 0210 0132 1945 3611Scaled Emot Effect 0118 00106 3386 00858 00984 0142 000251 1085 0265 00329 00524Scaled Neutral Effect 0159 0223 4014 00732 00974 0202 000934 0408 0202 00167 00257Obs 1777 1777 1773 1508 1777 1785 1764 1777 1762 1709 1732

Notes The ldquoemotionalrdquo treatment repeats the estate tax slide from the omnibus treatment but eliminates the rest of the treatment Theldquoneutralrdquo treatment is a version of the ldquoemotionalrdquo estate tax treatment that attempts to remove any framing effects All outcomes aredefined as previously ldquoCharitiesrdquo and ldquoEduc polrdquo refer to the ranking (from 1 to 5 with 1 being the highest ranking) that respondentsattribute to private charities and education policies as means to redistribute income The lower number of observations in column 4 isdue to the fact that this question was not asked in one smaller wave (sample of 300) lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

31

Appendix Table 14 Effect of estate-tax-only treatment on outcome variables (cont)

Min wage Aid Food stamps Housing Trust Govt scope No waste Dem 2014

(1) (2) (3) (4) (5) (6) (7) (8)

Treated (Emotional) 00529 0109 00982 0236lowastlowastlowast -00164 00172 -00281 00344[00865] [00837] [00861] [00824] [00205] [00585] [00303] [00213]

Treated (Neutral) -00838 00273 00628 0127 -000558 00259 -00587lowast -000310[00870] [00842] [00866] [00829] [00205] [00587] [00303] [00213]

Control mean 2608 2130 1797 1927 0153 3074 1456 0470Scaled Emot Effect 00913 00624 00534 0140 0235 00150 00896 00490Scaled Neutral Effect 0145 00156 00341 00755 00803 00225 0187 000441Obs 1495 1495 1495 1495 1756 1756 1754 1756

Notes See above ldquoNo wasterdquo takes values from 1 to 3 with 1 representing that the government is wasting a lot of tax revenue and 3that the government is not wasting much tax revenue at all Note that the only statistically significant effect for a poverty-relatedoutcome is for increased public housing We speculate that this effect is due to seeing the picture of the mansion in the ldquoemotionalrdquoestate tax treatment (but not in the neutral treatment) The lower number of observations in columns 1-4 is due to the fact that thesequestions were not asked in one smaller wave (sample of 300) lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

32

Appendix Table 15 Effect of trust treatment on outcome variables

Ineq v ser Ineq inc Pov v ser Deserving Top tax Mill tax Estate Petition

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00547lowast 00119 -000257 -00555lowastlowast 0490 -00421 -000168 -00602lowastlowast

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

Control mean 0343 0755 0383 0185 3470 0722 0204 0174Scaled Trust Effect 0182 0341 000828 0204 00452 00949 000728 0580Obs 899 899 899 899 898 899 895 899

Notes The negative trust prime treatment consists of several multiple-choice questions that made respondents reflect on aspects ofgovernment they dislike All terms are defined as previously lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

Appendix Table 16 Effect of trust treatment on outcome variables (cont)

Min wage Aid Food st Housing Trust Active No waste Dem 2014 Charity Educ pol

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Treated -000428 -0139lowastlowast -0153lowastlowast -0163lowastlowastlowast -00582lowastlowastlowast 00236 -00278 -00462lowast 0187lowastlowast 00615[00902] [00616] [00673] [00614] [00203] [00688] [00346] [00258] [00791] [00885]

Control mean 2673 2675 2454 2581 0125 3031 1423 0479 1800 3732Scaled Trust Effect 000531 0128 0119 0133 1730 00170 0109 00686 0169 0265Obs 899 899 899 899 899 899 898 899 850 874

Notes See above lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

33

Appendix Table 17 Effect of ldquoemotionalrdquo treatment on outcome variables

Ineq v ser Ineq inc Pov corr Childpov corr Min wage corr Pov vs Deserving Top tax Mill tax Estate Petition

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

Treated 00783lowastlowastlowast 00410 0258lowastlowastlowast -00717lowastlowast 00676lowastlowast 00885lowastlowastlowast -00131 0484 00316 00149 -00000573[00292] [00258] [00314] [00298] [00341] [00313] [00228] [1268] [00256] [00274] [00252]

Control mean 0337 0775 0442 0363 0302 0296 0173 3447 0728 0276 0184Scaled Poverty Effect 0221 0225 1754 1522 1105 0257 00413 00357 00589 00440 0000390Obs 1002 1001 999 994 799 799 1002 1002 1001 999 1002

Notes The ldquoemotionalrdquo treatment aimed at creating empathy between the respondent and families living in poverty Respondents weretold about poverty rates and had to fill out a minimum budget for a family like theirs living in the same city Respondents were then shownhow their minimum budget compared to the poverty line All outcomes are as defined previously The lower number of observations incolumns 5 and 6 is due to the fact that these questions were not asked in one smaller wave (sample of 200) lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

Appendix Table 18 Effect of ldquoemotionalrdquo treatment on outcome variables (cont)

Min wage Aid Food st Housing Trust Scope No waste Dem 2014 Charity Educ pol

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Treated 00469 0117lowast 0177lowast 00397 -000979 00537 -00655lowast 00120 00608 -0145lowast

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

Control mean 2546 2559 1832 2539 0124 3098 1420 0488 1929 3723Scaled Poverty Effect 00449 00714 00866 00291 00931 00352 0210 00181 00333 0204Obs 799 799 799 799 1002 1002 1002 1002 963 981

34

Appendix Table 19 Effect of policy treatment on outcome variables

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

Treated 00405 00206 00353 00369 0228lowastlowastlowast -000637 -000219 2023lowast 00311 -00217 -00222[00279] [00263] [00306] [00302] [00300] [00272] [00219] [1209] [00240] [00258] [00236]

Control mean 0343 0744 0415 0365 0355 0326 0180 3379 0713 0269 0187Scaled Policy Effect 0108 00892 0909 1056 7237 00196 000695 0140 00536 00642 0131Obs 1111 1111 1105 1107 1110 1111 1111 1111 1110 1110 1111

Notes The policy treatment aimed at creating empathy between the respondent and families living on a minimum wage Respondentshad to fill out a minimum budget for a family like theirs living in the same city Respondents were then shown how their minimumbudget compared to the minimum wage and how food stamps adds $150 per personmonth to the budget of such a family All outcomesare as defined previously lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

Appendix Table 20 Effect of policy treatment on outcome variables (cont)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Treated 0323lowastlowastlowast 0133lowastlowast 0313lowastlowastlowast 0176lowastlowastlowast -00325 00569 -00428 00248 -0137lowast -0117[00949] [00638] [00970] [00636] [00207] [00613] [00308] [00223] [00709] [00797]

Control mean 2546 2559 1832 2539 0149 3097 1394 0484 2025 3699Scaled Policy Effect 0310 00811 0153 0129 0654 00362 0125 00354 00740 0186Obs 806 806 806 806 1111 1111 1111 1111 1068 1085

Notes See above The lower number of observations in columns 1-4 is due to the fact that these questions were not asked in one smallerwave (sample of 300) lowastp lt 01lowastlowast p lt 005lowastlowastlowast p lt 001

35

How Elastic Are Preferences for Redistribution Evidence from Randomized Survey Experiments
- IenspThe Main Survey Experiment
- - A Data Collection
  - B The Omnibus Information Treatment
  - - IIenspData
    - - A Summary Statistics
      - B Survey Attrition
      - IIIenspResults from the Omnibus Treatment
        
        
        
        
        D Robustness Checks
        
        IVenspUnderstanding Our Results with Follow-up Surveys
        
        
        
        VenspConclusion
        
        REFERENCES

Page 2: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

By contrast top income tax rates as well as inheritance tax rates have fallen in the United States during this period3 While for institutional reasons the policy views of the majority might be ignored by policymakers (Bartels 2009) even more chal-lenging to the modelrsquos predictions is that survey respondents themselves show no increased demand for redistribution since the 1970s4 If anything the General Social Survey shows that there has been a slight decrease in stated support for redistribu-tion in the United States since the 1970s even among those who self-identify as having below average income (see Figure 1) These trends have led commentators to suggest that US residents simply do not care about rising inequality5

There are alternative explanations Americans may be unaware of the extent or growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011) this information may not be sufficiently salient or they are skeptical about the gov-ernmentrsquos ability to redistribute effectively6 In this paper we extensively examine

3 For top income tax rates see Piketty Saez and Stantcheva (2014) and for estate taxes see IRS calculations at httpwwwirsgovpubirs-soininetyestatepdf

4 See eg Kenworthy and McCall (2008) for evidence from a variety of OECD countries that saw increases in inequality but no corresponding increase in redistributive demand

5 As Newsweek put it in 2001 ldquoIf Americans couldnrsquot abide rising inequality wersquod now be demonstrating in the streetsrdquo Samuelson Robert J 2001 ldquoIndifferent to inequalityrdquo Newsweek May 7 p 45

6 A number of alternative theoretical models make different predictions than the median voter model Corneo and Gruumlner (2000) propose a model with status effects where the middle class opposes redistribution when this leads to more social competition with bottom income earners Alesina and Angeletos (2005) and Piketty (1995) show that different beliefs on the role of effort versus luck in success can lead to multiple redistributive equilibria Beacutenabou and Ok (2001) show that the prospect for upward mobility can limit the desire for redistribution There is also a wide empirical literature on the determinants of preferences for redistribution (see eg Corneo and Gruumlner 2002 Guillaud 2013 and Senik 2009 for evidence from cross-country survey data)

35

4

45

5

55

Gov

ernm

ent s

houl

d re

duce

inco

me

diffe

renc

es (1

minus7)

1980 1990 2000 2010

All respondents Self-identified below average income

Figure 1 The Government Should Reduce Income Differences (Scale from 1ndash7 GSS)

Notes This figure depicts responses since 1978 in the US General Social Survey (GSS) on whether the government should reduce income differences The empty diamond series is for all respondents while the full circle series is for respondents with below average income Regression fits are depicted for each series The graph uses the eqwlth vari-able from the GSS (though subtracts it from 8 so that it is increasing in support for redistribution)

A Data Collection

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 3: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

A Data Collection

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 4: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

A Data Collection

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 5: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

A Data Collection

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 6: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

A Data Collection

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 7: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

A Data Collection

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 8: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

II Data

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 9: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

B Survey Attrition

2176 1586

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 10: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

0288 0118 0238

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 11: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Coefficient P-value

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 12: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6)

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 13: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Treated 0931 00502 0357 00648 00325 minus00292 0132 00152[0549] [00126] [00140] [00156] [00141] [00115] [00339] [00125]

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 14: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 15: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

D Robustness Checks

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 16: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 17: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Increaseestate tax

Governmentscope

Trust government

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 18: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 19: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 20: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Estate tax corr

(1) (2) (3) (4) (5) (6) (7)

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 21: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 22: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 23: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6)

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 24: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 25: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Minwage

Aidpoor

Foodstamps Housing

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

Treated 00783 00410 00885 00469 0117 0177 00397 minus000979[00292] [00258] [00313] [00989] [00665] [0101] [00670] [00211]

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 26: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 27: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

V Conclusion

Povertyvery serious

Minwage

Aidpoor

Foodstamps Housing

Privatecharity

Trustgovernment

(1) (2) (3) (4) (5) (6) (7) (8)

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

REFERENCES

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 30: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 31: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 32: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Web Appendix of

Tax rate questions

1

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 33: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Political Outcomes

2

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 34: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

3

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 35: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

4

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 36: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

5

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 37: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

A5 Trust Experiment

6

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 38: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

7

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 39: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

8

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 40: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

9

10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

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10

11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

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11

12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

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12

13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

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13

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 45: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

14

15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

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15

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 47: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

16

Neutral Treatment

Control Group

4 of 11 41314 444 PM

17

18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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Neutral Treatment

Control Group

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17

18

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19

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health care

Rent

Food

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21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        REFERENCES

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18

Page Break

2 of 3 61514 643 AM

19

Rent

Food

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health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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Page Break

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19

Rent

Food

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20

health care

Rent

Food

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21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        REFERENCES

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Rent

Food

18 of 37 4214 1104 AM

20

health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        REFERENCES

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health care

Rent

Food

16 of 37 4214 1104 AM

21

Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        REFERENCES

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Observations 2417

22

23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        REFERENCES

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23

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

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        REFERENCES

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(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00144] [00128] [00114] [0549] [00126] [00140] [00156] [00141] [00141] [00151] [00115] [00339]

24

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 56: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8) (9)

25

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 57: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6)

26

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 58: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

27

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 59: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

Treated 000833 0102 00732 -00160 00589 00195 2440 2674[00809] [00770] [00716] [00786] [00799] [00785] [3602] [3547]

Control mean 0283 0218 0785 0756 0166 0128 3286 3076Obs 145 145 145 145 145 145 144 144

[00801] [00803] [00953] [00910] [00611] [00582] [0207] [0200]

Control mean 0758 0782 0180 0179 0122 0128 2995 2910Obs 145 145 145 145 145 145 145 145

28

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 60: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8)C L C L C L C L

[00129] [00128] [00120] [00117] [00122] [00121] [000970] [000970]

Control mean 0267 0293 0709 0743 0170 0192 0159 0159Obs 4547 4547 4546 4546 4519 4519 4546 4546

29

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 61: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

[00248] [00219] [00222] [00176] [00199] [00169] [1031] [0716] [00210] [00187] [00247] [00212]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00244] [00210] [00257] [00230] [00240] [00210] [00205] [00169] [00579] [00494]

30

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 62: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

31

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 63: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8)

32

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 64: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8)

[00311] [00289] [00313] [00239] [1326] [00275] [00266] [00236]

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 65: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

[00989] [00665] [0101] [00670] [00211] [00626] [00334] [00234] [00715] [00831]

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

Page 66: How Elastic Are Preferences for Redistribution? Evidence ...saez/kuziemko-norton-saez...growth of inequality (see Kluegel and Smith 1986 and Norton and Ariely 2011), this information

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

35

  - - IIenspData
        
        
        
        
        D Robustness Checks
        
        
        
        
        VenspConclusion
        
        REFERENCES

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